web programming 5 7 - fon.bg.ac.rs · proposal. er diagram – final version. transforming er...

Web Programming .................................................................................................................................. 5

XML Technologies and Applications...................................................................................................... 7

Time Series Analysis ............................................................................................................................... 9

Analysis and Logical Design of IS (project) ......................................................................................... 11

Data analysis.......................................................................................................................................... 13

Reliability and Risk Analysis ................................................................................................................ 15

Computer Architecture and Operating Systems .................................................................................... 17

Databases ............................................................................................................................................... 19

Biostatistics ........................................................................................................................................... 21

Digital Economics ................................................................................................................................. 23

User interface design ............................................................................................................................. 25

Dynamic of organizational systems ....................................................................................................... 27

Dicrete mathematical structures ............................................................................................................ 29

Distributed computer systems ............................................................................................................... 31

E-learning .............................................................................................................................................. 33

Econometrics ......................................................................................................................................... 35

Economics ............................................................................................................................................. 37

E-business .............................................................................................................................................. 39

Elements of the Theory of algorithms ................................................................................................... 41

English language for specific purposes 1 .............................................................................................. 43



Computer Systems Security .................................................................................................................. 49

Intelligent Systems ................................................................................................................................ 51

Internet of things ................................................................................................................................... 53

Internet marketing ................................................................................................................................. 55

Internet Technologies ............................................................................................................................ 57

Concurrent programming ...................................................................................................................... 59

Linear Statistical Models ....................................................................................................................... 61

Marketing .............................................................................................................................................. 63

Mathematics 1 ....................................................................................................................................... 65

Mathematics 2 ....................................................................................................................................... 67

Mathematics 3 ....................................................................................................................................... 69

Mathematics and music ......................................................................................................................... 71

Mathematical Logic with Applications ................................................................................................. 73

Mathematical Models of Efficiency ...................................................................................................... 75

Mathematical Software Packages .......................................................................................................... 77

Machine learning ................................................................................................................................... 79

Soft computing ...................................................................................................................................... 81

Management .......................................................................................................................................... 83

Human resource management ............................................................................................................... 85

Management of technology and development ....................................................................................... 87

Optimization Methods ........................................................................................................................... 89

Mobile business ..................................................................................................................................... 91

Mobile computing ................................................................................................................................. 93

Business Process Modeling ................................................................................................................... 95

Financial systems modeling .................................................................................................................. 97

Multimedia production .......................................................................................................................... 99

Multimedia .......................................................................................................................................... 101

Advanced .NET technologies .............................................................................................................. 103

Advanced Java Technology ................................................................................................................. 105

Numerical Analysis ............................................................................................................................. 107

Selected Topics in Information Systems ............................................................................................. 109

Operations research 1 .......................................................................................................................... 111

Operational Research 2........................................................................................................................ 113

Optimization in Natural Resources Management ................................................................................ 115

Fundamentals of Information and Communication Technologies ...................................................... 117

Fundamentals of Quality ..................................................................................................................... 119

Introduction to Game Theory .............................................................................................................. 121

Basis of Computer Geometry .............................................................................................................. 123

Organization Basics ............................................................................................................................. 125

Pedagogy with didactics ...................................................................................................................... 127

Legal Basis of Information Systems .................................................................................................... 129

Applied Operations Research .............................................................................................................. 131

Programming I ..................................................................................................................................... 133

Programming 2 .................................................................................................................................... 135

Programming data access .................................................................................................................... 137

Programming languages ...................................................................................................................... 139

Programming language translators ...................................................................................................... 141

Production systems .............................................................................................................................. 143

Information Systems Design ............................................................................................................... 145

Software design ................................................................................................................................... 147

Psychology .......................................................................................................................................... 149

Computer networks and telecommunication ....................................................................................... 151

Modern Software Architectures .......................................................................................................... 153

Simulation and simulation languages .................................................................................................. 155

Decision support systems .................................................................................................................... 157

Open source software .......................................................................................................................... 159

Software patterns ................................................................................................................................. 161

Software Engineering .......................................................................................................................... 163

Sociology ............................................................................................................................................. 165

Statistics .............................................................................................................................................. 167

Statistical Inference ............................................................................................................................. 169

Data Structures and Algorithms .......................................................................................................... 171

Probability Theory ............................................................................................................................... 173

Decision Theory .................................................................................................................................. 175

System theory ...................................................................................................................................... 177

Systems theory 2 ................................................................................................................................. 179

Introduction to Information Systems ................................................................................................... 181

Introduction to Combinatorial Optimization ....................................................................................... 183

Introduction to Mathematical Programming ....................................................................................... 185

Introduction to electronic business management ................................................................................. 187

Introduction to neural networks........................................................................................................... 189

Introduction to optimal control and game theory ................................................................................ 191

Introduction to fuzzy logic .................................................................................................................. 193

Supply Chain Management 1 .............................................................................................................. 195

Project Management ............................................................................................................................ 197

Risk management in e-business projects ............................................................................................. 199

Software Project Management ............................................................................................................ 201

Physical Project of IS in Selected Software Environment (project) .................................................... 203

Financial Management and Accounting .............................................................................................. 205

French for specific purposes 1 ............................................................................................................. 207



Heuristic methods ................................................................................................................................ 213

Programming 3 .................................................................................................................................... 216

Internship ............................................................................................................................................. 218

Final paper ........................................................................................................................................... 219

Study program / study programs:Information systems and technologies

Degree level: Undergraduate

Course:

Web Programming

Teacher:Đurić O. Dragan

Course status: Elective

ECTS points: 6

Prerequisites: none

Course objective

Mastering basic and advanced concepts of Web programming.

Learning outcomes

Students’ ability to implement Web applications on a widespread development platform , and to use appropriate software programming environments.

Course structure and content

Theoretical instruction:

Foundations. An example of a simple Web application. Web frameworks and the MVC pattern. Client Web application development. Data entry. Web forms. Entry validation. More complex Web applications. An example of a Web store. Integration with middleware and databases. Web components development. Localization and Internalization. Review.

Practical instruction:

Labs. Other forms of teaching. Research study work. Work with tools and frameworks. Practical project.

Web forms. Validation. Integration with middleware and databases. Web components development. Localization.

Literature/Readings

• Digital learning resources available on the course CD. • Examples of practical software projects.

• Open source software frameworks and tools, as well as their documentation and useful tutorials are freely available on the Web.

• Labs consists of practical work on students’ own projects under the supervision of the assistants.

The number of class hours per week Other classes:

– Lectures:

2

Labs:

2

Workshops:

-

Research study:

–

Teaching methods

Lectures and practical applications

Evaluation/Grading (maximum 100 points)

Pre-exam requirements Points Final exam Points

Participation in class Written exam

Participation in labs Project (implementation) 0 – 60

Project (conceptual solution) 0 – 40


Degree level: Undergraduate studies

Course:

XML Technologies and Applications

Teacher:Aničić M. Nenad

Course status: elective

ECTS points: 4 points

Prerequisites: /

Course objective

Student’s knowledge improvement in area of XML and providing new knowledge, techniques and skills for working with advanced technologies and applications based on XML.

Learning outcomes

Student will be capable to create, analyze, process and transform XML documents using advanced XML technologies. Also, student will be able to apply acquired knowledge in different implementation environments on all application architecture tiers (data storage tier, presentation tier, a domain logic tier)



XML basics (DTD, XML Schema). Connecting and navigation (XLink, XPointer, XPath). XML document transformation (XSLT). Displaying XML content on WEB (XHTML, CSS). XML data formatting (XSL-FO). Creating user interface for processing XML document (XForms). Tools for creating and processing XML. XML document parsing (DOM i SAX). Processing XML in Java. XML in application environments (Coocun, JSF, MyBatis, Hibernate, EJB). Using XML for data configuration and transport. Generating XML documents from object-relational databases. Storing and processing XML in databases. Semantic XML data models (RDFS, OWL). Exam preparation.


Basic concepts of XML documents: Making simple examples. Basic concepts of XML documents: Making more complex examples. XML document transformation using XSLT: Making simple examples. XML document transformation using XSLT: Making more complex examples. Displaying XML content on Web (XHTML, CSS). Formatting XML data using XSL-FO functions and data types. Using XForms for creating user interface. Parsing XML document using DOM and SAX: Making simple examples.

Parsing XML document using DOM and SAX: Making more complex examples. Displaying and using XML in application environments. Using SQL for generating XML from object-relational databases. Storing and processing XML in databases. XML and JavaScript. Using Web services for XML manipulation. Exam preparation.

Literature/Readings

1. Skonnard A., Gudgin M., Essential XML Quick Reference: A Programmer's Reference to XML, XPath, XSLT, XML Schema, SOAP, and More, Addison-Wesley Professional, Reading 2001.

2. Rusty Harold, E., Processing XML with Java, Addison-Wesley Professional, Reading 2002. 3. Kay M., XSLT: Programmer's Reference (Programmer to Programmer), Wiley Publishing,

Indianapolis 2003.


Lectures: 2 Labs: 2 Workshops: Research study:

Teaching methods

Lectures (30 classes) and labs (30 classes)



Colloquia 30 Oral exam 30

Seminar 50 Homework 20


Degree level: BSc

Course:

Time Series Analysis

Teacher:Bulajić V. Milica,Vukmirović V. Dragan


ECTS points: 4

Prerequisites:

Course objective

Introduction to concepts and methods of time series analysis. Qualifying for individual application of these methods for solving practical problems with the special emphasis to financial time series.

Learning outcomes Students will be capable of understanding the wide applicability of methods of time series analysis. Students will be prepared for time series application in process modeling.



L-01: The concept of random process. The classification of random processes. White noise. L-02: The Wiener process. The Markov process. The Markov chains. L-03: The stationary random processes. Spectral representation of random process.. L-04: The linear transformations of stationary processes. Martingale. L-05: The theory of waiting queues in networks. L-06: The time series. L-07: Stationarity. The correlation and autocorrelation function. L-08: Methods for analysis of stationary time series. L-09: The nonstationary time series. L-10: ARIMA models. L-11: The conditional heteroscedastic models, ARCH model. L-12: GARCH model and its modifications. L-13: Nonlinear models and theirs application. L-14: The analysis of multidimensional time series. L-15: The analysis of financial time series.


P-01: The concept of random process. P-02: The classification of random processes. P-03: The stationary random processes P-04: The linear transformations of stationary processes. P-05: The waiting queues. P- 06: The time series. P-07: The correlation and autocorrelation function. P-08: Methods for analysis of stationary time series. P-09: The nonstationary time series. P-10: ARIMA models. P-11: The conditional heteroscedastic models, ARCH model. P-12: GARCH model. P-13: Nonlinear models and theirs application. P-14: The analysis of multidimensional time series. P-15: The analysis of financial time series.

Literature/Readings

1. Kovaĉić, Z., Analiza vremenskih serija, Ekonomski fakultet, 1995.

2. Mališić, J., Jevremović, V., Statistička analiza i slučajni procesi, Nauĉna knjiga, Beograd, 1991. 3. Cryer, J. D., Chan, K. S., Time Series Analysis - With Applications in R, Springer, 2010.



Teaching methods

The traditional way of lecturing, with the use of whiteboard and computer



Participation in class 5 Written exam 25

Participation in labs 5 Oral exam 25

Colloqia 20

Seminar work 20



Course:

Analysis and Logical Design of IS (project)

Teacher:Aničić M. Nenad,Babarogić S. SlaĎan



Prerequisites: Introduction to Information Systems

Course objective

During this course students will learn to analyze and logically design information systems, using appropriate conventional and object-oriented models and methods.

Learning outcomes

Students will be qualified to analyze and specify user requirements independently, to model databases and applications using patterns and CASE tools by working in a project team.




Project topics selection. SSA first level. SSA – final decomposition. SSA - data dictionary. ER diagram – proposal. ER diagram – final version. Transforming ER diagram to relational model. IDEF1X. Conceptual class diagram. Use-case diagram. Detailed use-case specification. Sequence diagram. Final class diagram. Project revision.

Literature/Readings

1. George, Joey F., Batra, Dinesh, Valacich, Joseph S., Hoffer, Jeffrey A., Object-oriented systems analysis and design, Pearson Prentice Hall, 2004.

2. Hoffer, Jeffrey A., George, Joey F., Valacich, Joseph S., Modern systems analysis and design, Pearson Prentice Hall, 2005

3. Larman C., Applying UML and Patterns-An Introduction to Object-Oriented Analysis and Design, 3th ed., Prentice Hall, 2004.

4. Materials and scripts from lectures and labs, Laboratory for Information systems, FOS 5. e-Presentations on course site pisbp.fon.bg.ac.rs


Lectures: Labs: Workshops: Research study:

Teaching methods

Students are divided into groups and are mutually working on selected and approved topic. Each group has its mentor that each week in defined periods for this course controls and helps them in revision of results of analysis and logical design of IS in specific group domain.



Project development 100

Study program / study programs: IST

Degree level: Graduate studies

Course:

Data analysis

Teacher: Vukmirović V. Dragan


ECTS points: 4

Prerequisites: none

Course objective:

Studding data analysis techniques. Understanding the interconnections between statistical analysis, and methods and techniques for discovering new information from the databases.

Learning outcomes:

Training for data analysis, analysis of data structures, and a model construction. Training to draw conclusions based on the graphical analysis and data visualization.

Course structure and content:

Theoretical study:

T01: Classification of multivariate statistical analysis methods. Types of data and measurement scales. T02: Graphical analysis and data visualization. T03: Multidimensional data analysis. T04: Visualization of complex data and complex databases contents. Algorithms for data visualization. T05: The concept of knowledge discovery in databases. Classification. Estimate. T06: Prediction. Relations analysis. T07: Dependence modeling. T08: Detection of clusters. T09: Decision trees. Exploratory data analysis. T10: Evaluation of discovered knowledge. T11: The role of statistics in the process of knowledge discovery in databases. T12: Knowledge discovery in statistical databases. T13: Computer support statistical surveys. T14: Evaluation and testing. T15: Specific practical problems solving.

Practical study:

P01: Multivariate statistical analysis. P02: Types of data and measurement scales. P03: Graphical analysis and data visualization. P04: The visualization of complex data. P-05 to P-09: Methods and techniques of knowledge discovery in databases. P10: Evaluation of discovered knowledge. P11: The role of statistics in the process of knowledge discovery. P12: Knowledge discovery in statistical databases. P13: Computer support for statistical surveys. P14: Evaluation and testing. P15: Specific practical problems solving.

Literature/Readings:

1. Lohninger H., Teach/Me Data Analysis, Springer, 1999. 2. Vuković N., Statističko zaklјučivanje, FON, 2010. 3. Vuković N., PC statistika i verovatnoća, FON, 2005. 4. Kovaĉić Z., Multivarijaciona analiza, Ekonomski fakultet, 1994. 5. Kovaĉić Z., Analiza vremenskih serija, Ekonomski fakultet, 1995.


Lectures: 2 Practical work: 2 Other: Research study:

Teaching methods: Classic (ex-cathedra) using blackboard, computer, projector. Solving short case studies and practical work in computer room.



Colloquium – tasks 5 Written exam (alt. to coll. tasks) 25

Participation in labs 5 Oral exam (alt. to coll. theory) 25

Colloquium – theory 20

Seminar tasks 20


Degree level: undergraduate

Course:

Reliability and Risk Analysis

Teacher:Vujošević B. Mirko,Makajić-Nikolić D. Dragana


ECTS points: 5

Prerequisites: Probability Theory

Course objective

Course objective is to provide the students with: a) basic knowledge about reliability theory and possibilities of its application and achievements in solving practical engineering and managements problems, b) methods and approaches for practical reliability and risk assessment in the technical systems.

Learning outcomes

Students are trained to model real-life problems from the aspect of the system reliability, compute system reliability using modern methods and software packages, assess risks and determine corrective actions for achieving quality, high product reliability and risk management in all of the phases of the product life cycle.



Introduction to preliability theory. Basic reliability terms: fault, failure, reliability function, failure rate, mean time between failure. Block diagrams in reliability analysis; Event trees. Redundant systems and fault-tolerant systems. Maintainability, repair time, down time; system availability and system effectiveness. Modeling of repairable systems: Markov chains, Petri nets. Definition of risk. Approaches in risk management. Risk measurement. Risk assesment methods and techniques. Fault tree analysis. Failure mode and effect analysis. Hazard analysis. HAZOP study. Reliability of the complex systems; network reliability. Reliability and quality assesment of the software. Human reliability.


Plan is in accordance with theoretical instructions plan. Main topics of the practical instructions are standards and available software packages for solving case studies.

Literature/Readings

1. R. Petrović, M. Vujošević, D. Petrović, Optimizacija redundantnih sistema, Saobraćajni fakultet, Beograd, 1993.

2. S. Krĉevinac i dr, Operaciona istraživanja 2, FON, Beograd, 2013. 3. N. Vujanović, Teorija pouzdanoasti tehničkih sistema, Vojnoizdavaĉki i novinski centar, Beograd,

1990. 4. D. Kececioglu, Reliability Engineering Handbook, DEStech Publication, 2002. 5. P. D. T. O’Connor, Practical reliability engineering, Wiley, 2007 6. C. A. Ericson II, Hazard analysis techniques for system safety, Wiley, 2005


Lectures: 2 Labs: 1 Workshops: 1 Research study:

Teaching methods Theoretical classes – traditional. Practical classes manly with the use available software packages for reliability and risk analysis.




Participation in labs 20



Course:

Computer Architecture and Operating Systems

Teacher:Simić B. Dejan,Minović V. Miroslav,Milovanović M. Miloš

Course status: Compulsory

ECTS points: 6

Prerequisites: /

Course objective

To introduce students to the essential relationship that exists between the hardware and software, as well as balancing (cost/performance tradeoffs) computer architecture. To understand the concepts of organization and computer architecture, organization and principles of basic functional components of the operating system.

Learning outcomes

Students will gain the necessary knowledge in the field of computer architecture and organization, as well as an understanding of the basic concepts of modern operating systems for their effective use. In addition, students acquire basic practical skills to work under Linux.



L-01: Introduction to Architecture and Computer Organization, L-02: Processor and Memory, Instruction Execution, L-03: Types of Instructions, L-04: Addressing Modes, Instruction Formats, Interrupts, L-05: Flow of Control, L-06: Pentium and Multi-core Processors, Microprogramming Level, L-07: Introduction to Operating Systems, L-08: Process Management 1, L-09: Process Management 2, L-10: Memory Management 1, L-11: Memory Management 2, L-12: Processor Scheduling, L-13: Deadlock, L-14: Data Management, L-15: Data Security

Practical instruction: Exercises, Other forms of lectures, Research work

E-01: Basic terms in the field of computer architecture and organization, E-02: Characteristics of memory, memory classification, E-03: Exercises of repetition 1, E-04: Examples of instruction execution, E-05: Input-output devices and standard interfaces, E-06: Exercises of repetition 2, E-07: Basic terms in the field of operating systems, E-08: The boot process and configuration of the operating system, E-09: Linux operating system, E-10: Exercises of repetition 3, E-11: Distributed operating systems 1, E-12: Distributed operating systems 2, E-13: Data protection under Windows and Linux operating system, E-14: Introduction to Knoppix, E-15: Exercises of repetition 4.

Literature/Readings

1. Dejan Simić, Pavle Bataveljić, ―Computer Organization and Operating Systems‖, FON, 2011. 2. Andrew, S., Tanenbaum Structured Computer Organization Prentice Hall, 6th edition, 2012. 3. Silberschatz Avi, Galvin Peter, Gagne Greg ―Operating System Concepts‖ John Wiley & Sons, 9th

edition, 2013 4. John Hennessy, David A. Patterson, Computer Architecture: A Quantative Approach, Elsevier, Inc., 2012. 5. Shuangbao (Paul) Wang, Robert S. Ledley, Computer Architecture and Security: Fundamentals of

Designing Secure Computer Systems, John Wiley & Sons, 2013. 6. The material in electronic form, FON, Beograd, 2013.



Teaching methods

Lectures, Exercises, Practical Work, Consultation.







Course:

Databases

Teacher:Marjanović M. Zoran,Aničić M. Nenad,Babarogić S. SlaĎan

Course status: mandatory


Prerequisites: /

Course objective

Students will gain detailed knowledge about databases and database management systems.

Learning outcomes

Students will be capable to perceive all data requirements, to model database, to understand database architecture and its components, use query languages to access data and to develop applications for updating and displaying data from database.



Introduction: Database management systems. ER diagram: model concepts. ER diagram: constraints. Operations. Examples. Relational model. SQL: structure. SQL: constraints. SQL: operations. Object databases. Object-relational model. Active databases. XML as data model. Functions of database management systems. Database design: system and user requirements analysis. Conceptual modeling. Database design: relational normalization. Exam preparation.


Database management systems. ER diagram: making simpler models. ER diagram: making more complex models. Relational model: relational algebra. Relational calculus. SQL: structure. SQL: constraints. SQL: operations. SQL: examples. Object, object-relational and active databases. Examples. XML as data model. Functions of database management systems. Database design: system and user requirements analysis. Conceptual modeling. Database design: relational normalization. Exam preparation.

Literature/Readings

- Basic Literature:

1. Lazarević B., Marjanović Z., Aniĉić N., Babarogić S., Baze podataka, FON, 2010. - Additional Literature:

• Referenced literature at the end of each chapter of the basic literature



Teaching methods

Lectures (30 classes), labs (30 classes) and practical labs (15 classes).



Colloquia 30 Written exam 40

Seminar 20 Oral exam 10



Course:

Biostatistics

Teacher:Ţarković P. Miloš,Jovanović Milenković V. Marina,Jeremić M. Veljko


ECTS points: 4

Prerequisites: /

Course objective

Introduction to statistical evaluation of experimental studies and clinical studies. The application of statistical methods in biology and medicine.

Learning outcomes Students will be able to perform methodological research in biostatistics and related fields, as well to actively participate in state, national, and international statistical communities.



L01: Design of research studies and sampling. L02: Biostatistical methods. L03: Statistical methods in epidemiology. L04: Statistical methods in clinical studies. L05: Statistical inference. L06: Principles of epidemiology. L07: Survival analysis, L08: Categorical data analysis. L09: Longitudinal data analysis. L10: Multivariate analysis. L11: Cohort analysis. L12: Applied time series analysis. L13: Priority and post priority prediction. L14: Computer-supported statistical research. L15: Evaluation and testing.


P01: Practical work in design of research studies. P02: Case studies in design of research studies. P03: Implementation of biostatistical methods. P04: Case studies in biostatistics. P05: Application of survival analysis. P06: Kaplan-Meier analysis. P07: Cox regression. P08: Case studies in clinical studies. P09: Case studies in epidemiology. P10: Problems of forecasting. P11: Problems of evaluation. P12: Problems of testing. P13: Problems of foresight. P14: Practical problems resolving. P15: Practical problems resolving.

Literature/Readings

1. Sullivan M., Essentials Of Biostatistics, In Public Health, Jones & Bartlett Learning, 2nd ed, 2011.

2. Shahbaba B., Biostatistics with R: An Introduction to Statistics Through Biological Data (Use R!), Springer, 2012.

3. Motulsky H., Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, Oxford

University Press, 2nd ed, 2010. 4. Wayne W. D., Chad L. C., Biostatistics: A Foundation for Analysis in the Health Sciences,

Willey, 10th ed., 2013. The number of class hours per week Other classes:


Teaching methods

The traditional way of lecturing, with the use of whiteboard and computer.





Colloqia 20

Seminar work 20



Course:

Digital Economics

Teacher:Milićević K. Vesna,Ilić J. Bojan


ECTS points: 5

Prerequisites: none

Course objective

Acquisition of knowledge and skills in the field of the digital economy relevant in terms of the linkage of trends in contemporary business and changes in the field of information and communication technologies.

Learning outcomes

Competencies related to the complexity of business in terms of digitization.



Characteristics of the digital economy. Virtualization of business. Specific features of the electronic market. Value engineering. Adaptive efficiency of the digital economy. Performance measurement in the digital economy. The importance of external benchmarking. The virtual value chain and the benefits of outsourcing. Economics of information. The importance of information and communication technologies for creating competitive advantages. Network externalities and application of pricing methods. Methods of improving profitability in the digital economy. Application of software for the simulation of business operations results. Competitive strategies in the digital economy. Practical aspects of developing business plan for new business venture in the conditions of the digital economy.


Class exercises follow the content and structure of lectures and include: case study analysis, value engineering-method application, creative workshops, implementation of new approaches to measuring business performance in the digital economy, exercises using the Internet, the software application in the digital economy.

Literature/Readings

Milićević V., Internet ekonomija (selected chapters), Fakultet organizacionih nauka, Beograd, 2002.

Chaffey D., E-Business and e-Commerce Management, Strategy, Implementation and Practice (selected chapters), Prentice Hall, Financial Times, Harlow, 2011

McKenzie R., Digital Economy:How Information Technology has Transformed Business Thinking

(selected chapters), Praeger, Westport, Connecticut, London, 2003


Lectures:

2

Exercises:

2

Workshops: Research study:

Teaching methods

Lectures with the participation of students in interactive teaching, presentation of practical examples, case studies, exercises using the Internet, creative workshops, software application, exercises to solve specific business problems related to the digital economy, consultations in the preparation of seminar papers.



Participation in class 10 Written exam

Participation in labs Oral exam 55

Seminar paper 35



Course:

User interface design

Teacher:Minović V. Miroslav,Milovanović M. Miloš


ECTS points: 4

Prerequisites: /

Course objective

Objective of the course is to familiarize students with theoretical and practical approaches to user interface design.

Learning outcomes

Students will acquire basic knowledge and skills needed for designing and evaluating user interfaces for both desktop systems and mobile platforms.



P-01: Usability of interactive systems.P-02: Guidlines, principles and theories. P-03: Human computer interaction basics. P-04: Managing the design process. P-05: Development metodology. P-06: Interface design evaluation. P-07: Software tools. P-08: Direct manipulation and virtual environments.P-09: Menu selection, forms and dialog frames. P-10: Command and natural languages.P-11: Interaction devices. Cooperation.P-12: Quality of service.P-13: Functionality and look balance.P-14: Instructions for use, online help and learning manuals.P-15: Search and information visualisation.


V-01: Introduction to user interface design (available platforms and user interface design tools).V-02: User interfaces on the Internet (HTML/JavaScript/AJAX).V-03: User interfaces on the Internet (HTML5).V-04: User interfaces on the Internet (Java Applets and JavaFX).V-05: User interfaces on the Internet (ASP.NET and Silverlight).V-06: Desktop user interfaces (.NET Framework).V-07: Desktop user interfaces (JAVA SE (SWING)).V-08: Desktop user interfaces (Flex).V-09: Mobile application user interfaces (Windows Mobile). V-10: Mobile application user (J2ME).V-11 Mobile application user (iOS). V-12: Mobile application user (Android). V-13: Methods and techniques for checking user interface usability (cognitive walkthrough).V-14: Methods and techniques for checking user interface usability (focus group).V-15: Methods and techniques for checking user interface usability (thinking aloud)

Literature/Readings

1. B. Shneiderman, C. Plaisant (2005), Dizajniranje korisničkog interfejsa, CET, Beograd 2. Starčević, D., Štavljanin, V., (2013), „Multimediji―, FON, Beograd 3. Usability Engineering, Jakob Nielsen, Morgan Kaufmann, 1993


Lectures:

2

Labs:

2


Teaching methods

Lectures, labs



Homework 20 Written exam 50

Project 30



Course:

Dynamic of organizational systems

Teacher:Petrović J. Bratislav


ECTS points: 4

Prerequisites:

Course objective The aim of this course is to provide students with the fundamental concepts, methods and techniques for modeling, simulation and control of organizational systems and their application for solving practical business problems.

Learning outcomes The acquired knowledge will enable students to appropriately model, simulation and control practical business problems using ICT.



Problem definition and model. Mapping the structure of the system. Identification of inputs, flows and warehouses. Feedback. Path dependence. Networks. System modelling, Business process modelling. Business strategies and collaborations. Modelling of business systems. Modelling of financial systems. Modelling of social systems. Measuring of model performance. Model simulation. Forecasting and control.


Practical instructions closely follow the lectures. In the course, students gain hands-on knowledge and skills for solving practical problems using approapriate software packages (Matlab, Mathematica and SciLab).

Literature/Readings

1) B. J. Petrović, Teorija sistema, FON, 1998.

2) E. Sontag, Mathematical Control Theory, Springer, 1998.

3) M. Mesarovic, Y. Takahara, Abstract Systems Theory, Springer- Verlag, 1989.

4) Y. Takahara, M. Mesarović, Organization structure: cybernetics systems foundation, Springer, 2003.

5) C. G. Cassandras, S. Lafortune, Introduction to Discrete Event systems, Springer-Verlag, 2007.



Teaching methods

Lectures. In the course students gain hands-on knowledge and skills for solving practical problems using selected software packages (Matlab, Mathematica and SciLab). Mentoring. Project assignments for individuals or small groups.



Lab exercises 30 Written exam 30

Project presentation 40


Degree level: Undergraduate Studies

Course:

Dicrete mathematical structures

Teacher:Čangalović M. Mirjana,Manojlović P. Vesna

Course status: alternative

ECTS points: 5

Prerequisites: Mathematics 1

Course objective

The aim is to introduce students to some classical topics of Discrete mathematics (such as elements of mathematical logic and graph theory, relation structures, finite-state automata and formal languages) which are necessary for the profile of an engineer of informatics.

Learning outcomes

Students will be prepared for a formal way of thinking and making conclusions which represents a crucial basis of computer sciences.


Mathematical logic: Propositional logic, propositional formula, conjunctive and disjunctive normal forms, methods of proof in the propositional logic. Predicate logic, predicate formula, the truth value of the predicate formula, methods of proof in predicate logic. Relation structures: Relations and their properties, partially ordered sets, chains and lattices. Elements of the graph theory: Definition of the graph, directed and undirected graphs, paths in a graph, trees and their application to computer sciences. Mathematical machines: Finate-state machines and automata, minimization of the automaton, connecting automata in parallel and series. Formal languages and grammars: Alphabet, sentence, formal language, notion of a phrase-structure grammar, the language generated by the grammar, regular grammars and finite-state automata, Turing machine.

Literature

1. M. Ĉangalović, V. Kojić (Manojlovic), V. Baltić, Diskretne matematičke strukture, FON,

2009/14 2. V. Manojlović, M. Ĉangalović, Zbirka zadataka iz Diskretnih matematičkih struktura, FON,

2012 3. D. Stevanović, V. Baltić, S. Simić, M. Ćirić, Diskretna matematika-osnove kombinatorike i

teorije grafova, DMS, 2008 4. K.H Rosen, Discrete Mathematics and Its Applications, 4th edit, McGraw-Hill, 1999


Lectures:

2

Labs:

2


Teaching methods

Classical lectures illustrated by the corresponding software implementations


Pre-exam activities Points 40 Final exam Points 60

Activates during lectures 5 Written exam 20

Practical exercises 5 Oral exam 40

Colloquiums 20

Business game 50



Course:

Distributed computer systems

Teacher:Minović V. Miroslav,Milovanović M. Miloš


ECTS points: 4

Prerequisites: /

Course objective

Objective of the course is to familiarize students with theoretical and practical approaches to advanced distributed systems and Internet application protocols development.

Learning outcomes

Students will acquire basic knowledge and skills needed for advanced distributed systems (such as blockchain, P2P and CDN) and Internet application protocols development.



P-01: Introduction. P-02: Network model protocols and layers. P-03: Remote systems communication. P- 04: Resource naming. P-05: Remote systems synchronization. P-06: Error resistance.P-07: Material update - preparation for Colloquium.P-08: Distributed systems security and protection.P-09: Distributed filesystems. Consistency and replication.P-10: Distributed operating systems.P-11: Cluster computing.P- 12: Service oriented systems.P-13: Grid computing.P-14: Cloud computing.P-15: Systems virtualization.


V-01: Introduction.V-02: Using Wireshark tool for network traffic supervision.V-03: Programming remote processes communication.V-04: DNS service setup and configuration.V-05: Configuration and programming time synchronization.V-06: Programming distributed transactions.V-07: Developing fault- tolerant system architecture. V-08: Material update - preparation for Colloquium. V-09: VPN network setup and configuration.V-10: Distributed filesystem setup and configuration.V-11: Distributed operating system setup and configuration.V-12: Apache server configuration for aiding web services.V-13: Grid computing realization using PlanetLab platform.V-14: Cloud computing realization using Azure platform.V-15: Material update - preparation for exam.

Literature/Readings

1. Andrew S. Tanenbaum, Maarten van Steen (2006), Distributed Systems: Principles and Paradigms, Prentice Hall

2. Dušan Starčević i saradnici, Računarske mreže i telekomunikacije – praktikum, FON, Beograd, 2013.

3. James F. Kurose, Keith W. Ross (2009), Umrežavanje računara: od vrha ka dnu, CET, Beograd The number of class hours per week Other classes:

Lectures:

2

Labs:

2


Teaching methods

Lectures, labs




Project 40

Study program / study programs: Information systems and technologies


Course:

E-learning

Teacher: Gordana Đ. Milosavljević


ECTS points: 4

Prerequisites:

Course objective

Introduction to the role of technology enhanced learning within organization and its characteristics. Develop knowledge and skills for a wide application of information and communication technologies in education and learning. Learning outcomes

Students will be able to develop content for e-learning process, as well as to implement e-learning using specific tools.



The development of distance education. The basic conceptual definitions: e-education, e-learning, m-learning. Managing distance education system. Synchronization of distance education. The forms of mediation through information and communication technologies. Videoconferencing. Tools for e-learning. Models for e-learning. Personal e-learning environment. Using mobile technology for learning. Communication in e-learning. Psychological aspects of electronic communication. Designing education and information-communication technologies. Educational Software. The use of ICT for knowledge evaluation.


Practical application of: e-communication, Knowledge Management. Learning via the Internet and mobile technologies. Web 2.0 tools for e-learning. Learning Content management systems - Moodle.

Literature/Readings

1. Rosenberg m., "E-learning - Strategies for Delivering Knowledge in Digital Age", McGraw-Hill, 2001 2. Alan Clarke: „e-Learning Skills“, Palgrave Macmillan, 2004 3. Iverson, Kathleen M.: „E-learning Games : Interactive Learning Strategies for Digital Delivery“,

Pearson/Prentice Hall, 2005 The number of class hours per week Other classes:

Lectures:

2

Labs:

2


Teaching methods

Lectures, discussions, implementation of different e-leaning methods, creative workshops, exercises.



Essay 50 Written exam 50


Degree level: BSc

Course:

Econometrics

Teacher:Bulajić V. Milica,Radojičić A. Zoran,Vukmirović V. Dragan,Jeremić M. Veljko


ECTS points: 4

Prerequisites:

Course objective:

Introduction to econometric models- regression analysis, time series analysis, simultaneous equation models, and other econometric problems. Special attention is devoted to methods that are being used in financial management.

Learning outcomes

Students will be introduced to a broad range of applications of econometric models in different fields. They will be able to adequately employ econometric models to solve different econometric problems. Students will apply the statistical software package in solving these problems.



T01: Methodology of econometric research. T02: Linear regression models (LRM) and ordinary least square method (OLS). T03: LRM with two variables. Parameter estimation with OLS. T04: Statistical tests. Confidence intervals for parameters of LRM. T05: Predictions. Reduction of some non-linear models to linear models. T06: LRM with multiple variables. Dummy variables. T07: Multicolinearity, heteroscedasticity. T08: Autocorrelation. Generalized OLS. T09: Methods of simultaneous equations. T10: Parameter estimation with indirect method of least squares. T11: Parameter estimation with two-step method of least squares. T12: Time series. Components of time series. Analytical methods of trend detection. T13: Moving average methods. Methods of exponential smoothing. Holt-Winters method. T14: ARIMA models. T15: SPSS software package.


P01: Methodology of econometric research. P02: Linear regression model with two variables. Ordinary least square method (OLS). P03: Variance of estimates. Coefficient of determination P04: t-test and F- test. P05: Predictions. Reduction of some non-linear models to linear models. P06: LRM with multiple variables. P07: Dummy variables, multicolinearity. P08: Heteroscedasticity, autocorrelation. P09: Methods of simultaneous equations. P10: Parameter estimation with indirect method of least squares. P11: Parameter estimation with two-step method of least squares. P12: Time series. P13: Methods of time series analysis. P14: ARIMA models. P15: SPSS software package.

Literature/Readings

1. Mladenović Z., Nojković A., Zbirka rešenih zadataka iz ekonometrije, Ekonomski fakultet, 2011.

2. Vuković N., PC statistika i verovatnoća, FON, 2005. 3. Kovaĉić Z., Analiza vremenskih serija, Ekonomski fakultet, 1995. 4. Gujarati D., Basic Econometrics, McGraw-Hill, 2004. 1. Vuković N., Vukmirović D., Radojiĉić Z., SPSS praktikum, FON, 2003



Teaching methods: Traditional with the use of whiteboard and computer





Colloquium 20

Seminar 20


Degree level: undergraduate studies

Course:

Economics

Teacher:Kragulj P. Dragana,Jednak J. Sandra

Course status: compulsory

ECTS points: 6

Prerequisites: none

Course objective.

GaininGaining fundamental knowledge of economics (an introduction to the economic analysis, microeconomics and macroeconomics) through the theory, techniques and practical examples. The course is an introduction and foundation for related courses in higher years of study.

Learning outcomes

Introduction to economic science; elucidation and mastering basic economic categories and economic laws; linking economic concepts as abstract categories with practical economic life; proper orientation in identifying important economic events in one country, but also on a global level; development of economic logic and thinking about contemporary economic trends.



Introduction to economic science; The scope and the method of economics; Economic categories and economic laws; A review of the major schools of economic thought; Production, consumption, distribution and exchange; Factors of production and their interrelationship; Production possibilities frontier; Trade-off; The production function; The law of diminishing returns; Total, average and marginal product and their interdependence; Production and costs; Analysis of the markets of the factors of production; Capital and labor; Salary and profit; Firms in the market economy; The main macroeconomic aggregates; Gross domestic product, gross national product and national income; Market, prices and competition; Demand and supply of goods and services; Elasticity of demand and supply; Market equilibrium; Definition of the market and it's functions; Spheres of market inefficiency; Market structure; Maximizing target functions of the producers in the conditions of perfect and imperfect competition; Monopoly; Monopolistic competition; Monopoly price and profit; Aggregate demand and aggregate supply; Curve and the determinants of aggregate demand; Curve and the determinants of aggregate supply; The equilibrium of aggregate demand and aggregate supply; Accumulation, investment, consumption and national income; Determinants of national income; The use of accumulation; Accumulation curve and consumption curve; Accumulation and investments; Capital coefficient, average capital coefficient and marginal capital coefficient; Investment performance and capital coefficient; Consumption plus investment; Recessionary and inflationary gap; Inflation and economic development; Inflation and unemployment; Anti-inflation policy; Deflation; Macroeconomic stabilization policy; The labor market; Economic growth and development; Concept, importance, objectives and factors of economic growth and development; Indicators of development; The most important theories of economic growth and development; Characteristics of contemporary economic growth and development; Economic cycles; Anti-cyclical policies; Macroeconomic objectives and macroeconomic instruments; Correlation

between macroeconomic objectives and instruments; Economic functions of contemporary economy; Monetary and credit policy; Money market; Budget and tax policy; Investment policy; Incomes policy; Price system and price policy; Economics of open economy; International flows of goods and services; Nominal and real exchange rate; Devaluation and revaluation; Balance of payments; The European integration processes; The European Union; European transition processes; Macroeconomic problems of countries in transition; International capital movements; Foreign direct investments.


Seminar classes follow the methodical units lectures.

Literature/Readings

Kragulj D., Ekonomija - Osnovi mikroekonomske i makroekonomske analiza, izdanje autora, Beograd 2013.


Lectures:

2

Labs:

2


Teaching methods

Lectures, exercises, presentations of seminar papers and essays, case studies, tests, consultation. All form of teaching requires preparation, cooperation and participation of students. Students are encouraged and activated through interactive classes.



Participation in class 5 Oral exam 50

Seminar paper/Essay and their presentation

5

Colloquium 40



Course:

E-business

Teacher:Radenković LJ. Boţidar,Despotović-Zrakić S. Marijana,Bogdanović M. Zorica,Barać M. Dušan,Labus B. Aleksandra,Krčo M. SrĎan,Vukmirović V. Dragan,Vasković R. Vojkan

Course status: Compulsory / Alternative

ECTS points: 6/5

Prerequisites:

Course objective

The aim of this course is to introduce models, forms and e-business infrastructure to students in order to enable the use of such systems in practice

Learning outcomes

Students are enabled for projecting and implementation of e-business systems.



E-business - state and perspectives. Virtual organizations. Business models on the Internet. Revenue models. Electronic retail. B2B electronic commerce. Interoperability in e-business. E-government. E- Health. E-education. E-recruitment. Application of mobile services and mobile technologies in e- business. Mobile commerce. Supply chain management. Customer relationship management. Business Intelligence. Project management in e-business. Risk management in development and implementation of e-business systems. Managing e-business infrastructure. Semantic Web. Information integration. Standards and quality management. Key performance indicators. Legal and ethical aspects of e-business. Trends in electronic business.


Introduction. Distance learning system Moodle. Web sites development. HTML5. CSS3. The interactive elements of Web sites. JavaScript. JQuery. Web portal development. Content management system WordPress. Electronic stores development. Integration of electronic stores in a web portal. Customer relationship management. Integration of CRM in a web portal. SugarCRM.

Literature/Readings

1. E-resources from web site www.elab.rs

2. Editors M. Ivković, B. Radenković, Internet and modern business, monography, Faculty of Engineering „Mihajlo Pupin“, Zrenjanin 1998.

3. D. Chaffey, E-Business and E-Commerce Management (4th Edition), Prentice Hall, 2009.

4. A.Afuah, C.L.Tucci, Internet business models and strategies: text and cases, McGraw-Hill, 2003.



Teaching methods

Lectures, exercises, case studies, lab exercises in classrooms with computers, project / seminar papers, distance education.



Assignments 40 Written exam 20

Project 40



Course:

Elements of the Theory of algorithms

Teacher:Stojanović A. Milica


ECTS points: 4

Prerequisites: none

Course objective Presentation of the basic elements of the numerical complexity and analysis of the algorithms. Teaching students to make algorithms in different fields (graph theory, algebra, geometry, sequences, set theory)

Learning outcomes After course, students will be able to create algorithms and to determine their numerical complexity.



1. Time and space complexity of an algorithm and a problem. 2. Deterministic and nondeterministic Turing machine. 3. NP class of problems. 4. NP completeness and NP hard problems. 5. Construction of algorithms by the induction, examples. 6. Proving correctness of the algorithm. 7. Algorithms on the graphs: detour in graph; the shortest paths. 8. Transportation network; Hamiltonian paths. 9. Geometrics algorithms: problems with polygon. 10. Convex hull. 11. Algebraic algorithms: problems with polynomials. 12. Problems with matrices. 13. Algorithms over sequences and sets. 14. Seminar work.


Creating algorithms in field which were studied theoretically and analysis of their complexity

Literature/Readings

1. M. Ţivković: Algorithms, Math. Faculty, Belgrade, 2000. (in Serbian) 2. Z. Ognjanović, N. Krdţavac: Introduction into theoretical computer science, FON, Belgrade, 2004.

(in Serbian) The number of class hours per week Other classes:


Teaching methods: mentor and/or classical




Participation in labs Oral Exam 25

Projects 35



Course:

English language for specific purposes 1

Teacher:Jakić D. Gordana

Course status: Required

ECTS points: 2

Prerequisites: /

Course objective

Introduction to the basics of English for specific purposes in organizational sciences, systematic expansion of subject-related vocabulary, terminology, revision of grammar and development of students' formal business correspondence skills in the English language. The course enables systematic improvement of language competences and productive language skills and provides a foundation for further academic and professional upgrade.

Learning outcomes

Students will be able to understand subject-related written and spoken language production, take part in discussions and oral presentations (e.g. job interviews, meetings, negotiations) and produce grammatically correct and coherent writing, particularly related to the job application process (CVs, cover letters, job application letters, motivation letters, etc.).



Globalization; basic terms; History and the Present of Business; basic business terms; Starting up and Growing a Business; basic financial terms; describing trends; Organization; basic terms related to organization; Management and Its Functions; Managerial terms, collocations; A Brief History of PCs; basic ICT-related terms; The Internet; Internet and www-related expressions and affixes; On the Way to Work; basic terms and expressions to describe education and employment; Advertising a Job & Applying for a Job; phrases related to job seeking; On the Job; phrases related to employment and workplace; Business Letters, Emails and Presentations: structure, layout and content; Meetings and Negotiations; types of meetings, useful expressions;


Numbers and figures; raise vs rise; Overview of present tenses; Expressing the past; job vs work, stakeholder vs shareholder; Expressing the future; affect vs effect, stuff vs staff, personal vs personnel; Reported Speech; Extension of managerial and financial vocabulary, Conditionals; Basic ICT-related collocations and phrasal verbs; Infinitive vs Gerund, Use of Articles; Pronouncing symbols and characters; Passive Voice; Cover Letter, Curriculum Vitae (CV), Application Form; Personality adjectives; Employment, enquiry, request and complaint letter; Useful phrases for business email writing, running and attending meetings and telephone calls; Improving presentation skills; General Revision.

Literature/Readings

Jakić, G., AnĊelković, J., Novaković, M.: Organize Your English, Faculty of Organizational Sciences, University of Belgrade, 2013.

Oxford Dictionary of Business, Oxford University Press, Oxford, 2004.

McCarthy, C.: Cambridge Grammar of English, Cambridge University Press, Cambridge, 2002.



Teaching methods

Lectures, analysis of texts in English, exercises, pair work, team work, discussion, presentations, case studies, business essay writing, role-play.







Course:




ECTS points: 3

Prerequisites: /

Course objective

Further upgrade of language competences and productive language skills acquired during the course in English language for specific purposes I. Systematic expansion of terminology, vocabulary and language structures related to the subject field of organizational sciences, i.e. management and information systems and technologies.

Learning outcomes

Students will be able to understand more complex subject-specific written and spoken language production, take part in discussions and oral presentations and produce grammatically correct and coherent subject-related writing (e.g. press releases, reports, summaries, etc.) and confidently use subject-related terminology in English.



Computers – reading comprehension and discussion; Information Systems – reading comprehension and discussion; Computer Software – reading comprehension and discussion; Computer Programming – reading comprehension and discussion; The Internet – reading comprehension and discussion; Internet Addiction – reading comprehension and discussion; Computer Crime and Malicious Computer Programs – reading comprehension and discussion. Management – reading comprehension and discussion; Marketing – reading comprehension and discussion; Sales and Marketing – reading comprehension and discussion; Advertising – reading comprehension and discussion; Public Relations – reading comprehension and discussion; Finance – reading comprehension and discussion; Assets and Liabilities – reading comprehension and discussion; Accounting and Bookkeeping – reading comprehension and discussion.


Computers – vocabulary extension; Information Systems – vocabulary extension; Computer Software – vocabulary extension; Computer Programming – vocabulary extension; The Internet – vocabulary extension; Internet Addiction – vocabulary extension; Computer Crime and Malicious Computer Programs – vocabulary extension. Management – vocabulary extension; Marketing – vocabulary extension; Sales and Marketing – vocabulary extension; Advertising – vocabulary extension; Public Relations – vocabulary extension; Finance – vocabulary extension; Assets and Liabilities – vocabulary extension; Accounting and Bookkeeping – vocabulary extension.

Literature/Readings

Jakić, G., AnĊelković, J., Novaković, M.: Organize Your English, Faculty of Organizational Sciences, University of Belgrade, 2013.

Oxford Dictionary of Business, Oxford University Press, Oxford, 2004.

McCarthy, C.: Cambridge Grammar of English, Cambridge University Press, Cambridge, 2002.



Teaching methods








Course:




ECTS points: 4

Prerequisites: Exams in English language 1 and English language 2 successfully passed

Course objective

The course introduces the basics of academic language, provides an overview of techniques, strategies, genres, content and context necessary for producing well-written and well-structured academic discourse.

Learning outcomes

Students will be able to employ a wide variety of pre-reading and pre-writing techniques (skimming, scanning, brainstorming, note-taking), demonstrate clear and structured composition skills (sentence level to text level) be able to edit, proofread and critically evaluate different academic genres. Students will develop academic presentation skills that will enable them to give clear, concise and effective presentations.



Discussion, reading comprehension and the study of vocabulary, terminology, phrases, collocations and compounds that belong to the following topics: Management; Information Systems and Technology; Operations Management; Quality Management; Corporate Strategy and Structure; Entrepreneurship; E- commerce; Logistics and Supply Chain Management; Production Systems; Why Standards Matter; Computer integrated Manufacturing; Networks; Kaizen, JIT and Six Sigma; General revision.


Extension of vocabulary and terminology by using a case study and discussion methods; Topics include: Management; Information Systems and Technology; Operations Management; Quality Management; Corporate Strategy and Structure; Entrepreneurship; E- commerce; Logistics and Supply Chain Management; Production Systems; Why Standards Matter; Computer integrated Manufacturing; Networks; Kaizen, JIT and Six Sigma; Trends in organizational sciences: students’ presentrations.

Literature/Readings

Jakić, G.: Reading Texts, Faculty of Organizational Sciences, University of Belgrade, 2013.

J. McCarthy, J. McCarten, D. Clark, R. Clark, Grammar for Business, Cambridge University Press, Cambridge, 2009.

M. Landa, Privredno - poslovni reĉnik. Grafiĉka knjiga, Beograd, 2004.

P. Emmerson, Business Vocabulary Builder, Macmillan Education, Oxford, 2009.

S. R. Esteras, E. M. Fabre, Professional English in Use: ICT, Cambridge University Press, Cambridge, 2009



Teaching methods








Course:

Computer Systems Security

Teacher:Simić B. Dejan


ECTS points: 4

Prerequisites: /

Course objective

The course objective is to work with the basic concepts of protection of computer systems from end to end. Introducing students to new security threats and risks, as well as techniques to protect computer systems on concrete examples. Increasing awareness of the already existing, as well as new potential threats and attacks primarily in the Internet environment, as well as expanding knowledge of new tools to detect vulnerabilities of modern systems and the application of preventive protection. Learning outcomes

Students will gain fundamental knowledge in the field of computer systems security on concrete examples. Students will acquire an understanding for the vulnerabilities of modern web-based application and services, and discuss countermeasures. Students will gain a technical understanding of the main cryptographic concepts and technologies available today, including symmetric and asymmetric encryption, hashing, and digital signatures.


Theoretical instruction: L-01: Introduction to Computer Systems Security. L-02: Security threats and risks. L-03: Attack Methodology Analysis. L-04: Access Control Mechanisms. L-05: Security Models. L-06: Physical Protection. L-07: Hardware Protection. L-08: Basic Security Mechanisms. L-09: Introduction to Cryptography. L-10: Applying Cryptography. L-11: Digital signature and digital certificates. L-12: Network security. L-13: Application Security. L- 14: Security of Electronic Payment Systems. L-15: Review of previous lectures and preparing for the exam.


Exercises, Other forms of lectures, Research work: E-01: Basic terms in Computer Systems Security. E-02: Methods of Social Engineering. E-03: Methods of Risk Management. E-04: Methods of phishing. E-05: Examples of viruses and antivirus software. E-06: Examples of Trojan Horses. E-07: Examples of computer worms. E-08: Kerberos. E- 09: Examples of Applied Cryptography. E-10: Examples of applications of digital signature and steganography. E- 11: Authentication Methods. E-12: Applying Smart Cards. E-13: Applying PKI. E-14: Applying Firewalls. E-15: Review of previous excercises and preparing for the exam.

Literature/Readings

1. Stallings W., Network Security Essentials: Applications and Standards, Pearson Education Limited, 2013. 2. Stallings W., Brown L. Computer Security – Principles and Practice, Pearson, Prentice Hall, New Jersey,

2nd edition, 2011. 3. Dieter Gollmann, Computer Security, Third Edition, John Wiley & Sons, Ltd., 2011. 4. David Cowen, Computer Forensics InfoSec Pro Guide, McGraw-Hill Osborne Media, 2013. 5. The material in electronic form, FON, Beograd, 2013.



Teaching methods Lectures, Exercises, Practical Work, Consultation.






Degree level: BSc

Course:

Intelligent Systems

Teacher:Devedţić B. Vladan,Jovanović M. Jelena,Tomić B. Bojan,Ševarac V. Zoran

Course status: required

ECTS points: 6

Prerequisites: -

Course objective

Mastering concepts, techniques, languages and tools for development of intelligent software systems.

Learning outcomes

Experience with fundamental concepts and technologies of intelligent software systems, as well as development of skills needed to build and apply these systems.



Artificial intelligence and intelligent systems: basic concepts and overview of the field. Rule-based knowledge representation. Rule-based reasoning. Machine Learning. Supervised learning. Unsupervised learning. Neural Networks. Natural language analysis, processing and understanding: techniques and tools. Knowledge representation and reasoning on the Web. Semantic Web: basic concepts and technologies. Semantic annotation of content on the Web.


Introduction to software frameworks, tools and / or services specific to each of the areas to be presented in class. All software frameworks with which the students will work are open source and based on the Java programming language; all the services that will be introduced are based on the RESTful paradigm.

Literature/Readings � V. Devedzic, Intelligent information systems, digit / FON, Belgrade, 2000. � Resources available at http://is.fon.rs � S. Russell, P. Norvig, Artificial Intelligence - A Modern Approach, The 3rd Edition. Prentice Hall,

Englewood Cliffs, NJ, 2009. � Documents and tutorials related to software frameworks, tools and services covered in the labs. The number of class hours per week Other classes:


Teaching methods

Lectures: slides and practical case studies related to the discussed technologies of artificial intelligence and intelligent software systems. Labs: the tutor develops practical programs/systems or explains specific practices, the students follow and discuss details of the program with the tutor.



Project 0-20 Written exam 0-80



Course:

Internet of things

Teacher:Radenković LJ. Boţidar,Labus B. Aleksandra,Krčo M. SrĎan


ECTS points: 5

Prerequisites:

Course objective: The aim of this course is to introduce hardware and software infrastructure of Internet of things to students in order to enable them to develop and implement smart environments.

Learning outcomes:

Students gain theoretical and practical knowledge related to development and implementation of Internet of things applications.



Introduction to Internet of things. Wireless sensor networks: architecture, technologies, main problems, development platforms. Standardization. Designing smart environments: smart houses, smart classrooms and smart offices. Smart cities. Smart networks. Smart traffic, automation of traffic signals and parking. Smart e-government. Web and mobile technologies in automation of smart environments. Use of Internet of things in medicine. Overview of projects in the field of Internet of things.


Use of Linux operating system as a platform for development of smart environments. Scripts for interaction of automation systems. Designing hardware and software architecture for automation system. Communications and energy infrastructure as a basis for collection, transmission and processing of sensor data. Raspberry Pi platform. Introduction in Python programming language. Developing Python application to control the smart environment and collect sensor data. Use of open source Arduino platform for working with analog sensors. Design and implementation of web applications for automation: smart house, smart classroom or smart office. Design and implementation of mobile applications for automation: smart house, smart classroom or smart office. SMS and IVR application for automation: smart house, smart classroom or smart office.

Literature/Readings

1. E-resources, available at www.elab.rs. 2. Editor(s): Marijana Despotović-Zrakić, Veljko Milutinović, Aleksandar Bjelić. „High

performance and cloud computing in scienctific research and education“, IGI Global, 2014. 3. Greg Milette, Adam Stroud. „Professional Android Sensor Programming“, John Wiley & Sons,

Inc., 2012. 4. Jean-Philippe Vasseur, Adam Dunkels. „Interconnecting Smart Objects with IP“, Elsevier, Inc.

2010. 5. Klaus Finkenzeller. „RFID Handbook Fundamentals and Applications in Contactless Smart

Cards, Radio Frequency Identification and Near-Field Communication (Third Edition)“, John Wiley & Sons, Inc. 2010.

6. Mike Riley. „Programming Your Home Automate with Arduino, Android, and your Computer“, The Pragmatic Programmers, LLC. 2012.

7. David Boswarthich, Omar Elloumi, Olivier Hersent. „M2M Communications A Systems Approach“, John Wiley & Sons, Ltd. 2012.

8. S. Sitharama Iyengar, Nandan Parameshwaran,Vir V. Phoha, N. Balakrishnan, Chuka D. Okoye. „Fundamentals of Sensor Network Programming Applications and Technology“, John Wiley & Sons, Inc. 2011.

9. FP7 SENSEI deliverables: www.sensei-project.eu. The number of class hours per week Other classes:

Lectures: 2 Labs:2 Workshops: Research study:

Teaching methods





Seminar paper 40



Course:

Internet marketing

Teacher:Bogdanović M. Zorica,Labus B. Aleksandra,Vukmirović V. Dragan,Janičić R. Radmila


ECTS points: 5

Prerequisites:

Course objective

Aim of the course is to introduce Internet marketing concepts, business models for Internet appearance and techniques to students.

Learning outcomes

Students are enabled for implementation of Internet marketing plan.



Principles of marketing. Models of business performance on the Internet. Internet marketing plan. Internet marketing strategies. Techniques and tactics. SEO techniques. Social Media. Social networks. Mobile marketing. Customer relationship management. Business Intelligence in Internet marketing. Trends in Internet marketing.


Technologies of Internet marketing: forum, blog, RSS, CMS, affiliate, SEO, Google services. Internet business plan. Internet marketing plan. Domain registration, free hosting, paid hosting. Web Design, Study of visual identity. Wordpress CMS installation. Development of portal. SEO-example in Wordpress. CRM integration with WordPress. Integrating electronic store with WordPress. Use of Google services and social networks. Internet advertising. Web projects.

Literature/Readings

1. E-resources, available at www.elab.rs 2. Internet i savremeno poslovanje, monografija, editori M. Ivković, B. Radenković, Tehniĉki fakultet

„Mihajlo Pupin“, Zrenjanin 1998. 3. D. M. Scott, The New Rules of Marketing and PR, John Wiley & Sons 2007 4. D.Chaffey, Internet Marketing: Strategy, Implementation and Practice (3rd Edition), Prentice Hall

2006.

J. Strauss, A. El-Ansary, R.Frost, E-Marketing 4/E, Prentice Hall 2006.



Teaching methods




Assignements 40 Written exam 20

Project 40



Course:

Internet Technologies

Teacher:Radenković LJ. Boţidar,Despotović-Zrakić S. Marijana,Bogdanović M. Zorica,Barać M. Dušan,Krčo M. SrĎan


ECTS points: 6

Prerequisites:

Course objective

The aim of the course is to introduce the principles of design and development of applications in Internet environment to students. Studying models, architectures and techniques from conceptual and practical aspects, students are enabled to develop web applications.

Learning outcomes

Students acquire knowledge and skills related to design and implementation of information systems in Internet environment. Students have mastered basic techniques, methods and concepts of web application development.



Introduction, reference models and standards in computer networks. Internet as infrastructure for information transmission and delivery. Elimination of anomailes in application layer of TCP/IP model by introducing Internet technologies for session and presentation layers. Virtual private networks. Principles of application development in Internet environment. Use of HTTP as a transport layer emulation. XML technologies for storing, processing and visualization of data from presentation layer. JSON. Internet technology for providing distributivity, scalability and reliability in e-business applications. Service- oriented architecture. Principles of design and development of distributed e-business systems based on service-oriented architecture. Process- oriented modeling. Application servers. Cloud Computing. Semantic web and data visualization on web. Internet of things. Comparative review of technologies for development of information systems in Internet environment. Microsoft .NET technology. Java technology, PHP. Concluding remarks and directions for further development of Internet technologies.


Designing user interface elements. HTML5. JavaScript and jQuery technologies. Storage and transmission of data in a web environment. XML technologies. JSON technologies. JqGrid. AJAX. Implementation of business logic. Web application development. PHP. Object-oriented PHP. Data layer implementation. MySQL. PHP application development with MVC architecture. Service-oriented architecture. Web services. Data visualization on the web.

Literature/Readings

1. E-resources, available at www.elab.rs 2. Internet i savremeno poslovanje, monografija, editori M. Ivković, B. Radenković, Tehniĉki fakultet

„Mihajlo Pupin“, Zrenjanin 1998. 3. Despotović-Zrakić M., Milutinović V., Belić A. (Eds), High performance and cloud computing in

scientific research and education, monografija, IGI Global, 2014. 4. D.Ince, Developing Distributed and E-commerce Applications, Pearson Education Limited 2002.

ISBN: 978-0321154224 5. J. F. Kurose, K. W. Ross. Umreţavanje raĉunara: od vrha ka dnu sa Internetom u fokusu. Beograd:

Raĉunarski fakultet : CET, 2005., ISBN: 978-8679913395 The number of class hours per week Other classes:


Teaching methods





Web project 40



Course:

Concurrent programming

Teacher:Radenković LJ. Boţidar,Krčo M. SrĎan


ECTS points: 5

Prerequisites:

Course objective Aim of the course is to study methods, technological infrastructure and software tools used in development and implementation of distributed computer systems and concurrent programming

Learning outcomes

Students gain theoretical and practical knowledge that are necessary for development and implementation of distributed computing systems and concurrent programming.



Rationale multiprogramming system, hardware innovations. Kernel of multi-system, Examples of competing programs. Flunn's classification, MIMD machines. Typical multiprocessors. Distributed Computing Systems, components of distributed computing systems. Typical problems of communication and synchronization process. Architectural tools for controlling access to a critical region. Monitors. Concurrent programming in JAVA. Concurrent Programming in C++ language. Coordination and synchronization of processes in distributed computing systems. Service-oriented architecture and distributed business logic. Current trends in distributed and concurrent programming.


Concepts of coordination and synchronization in the C programming language, operating system UNIX, and Windows. Examples of concurrent programs in Java programming language. Coordination and synchronization of processes in the ORACLE DBMS

Literature/Readings

1. E-resources, available at www.elab.rs 2. Despotović-Zrakić M., Milutinović V., Belić A. (Eds), High performance and cloud computing in

scientific research and education, monografija, IGI Global, 2014. 3. M. Ben-Ari , Principles of concurent and distributed programming, New York: Prentice-Hall 1991. 4. Fred B. Schneider, On Concurrent Programming, Springer 1997. The number of class hours per week Other classes:


Teaching methods





Project 40


Degree level: BSc

Course:

Linear Statistical Models

Teacher:Bulajić V. Milica,Radojičić A. Zoran,Jeremić M. Veljko

Course status: Alternative

ECTS points: 5

Prerequisites:

Course objective

Introduction to multivariate statistical analysis and the implementation of adequate methods in practical problems solving, with an emphasis on the preparation and interpretation of results of model’s transformation, model evaluation, algorithms, and software packages for multivariate statistical analysis.

Learning outcomes

Students will be capable of conducting statistical research and using modern statistical methods in different areas. Students will apply the statistical software package in solving these problems.



L01: Generalized matrix and systems of linear equations. L02: Multidimensional normal distribution. P03: Principal component analysis. L04: Testing and selection of principal components. L05: Interpretation and analysis of principal components in SPSS. L06: Factor analysis. L07: Rotation of factors. Methods of orthogonal and non-orthogonal rotation. L08: Factor scores and methods for their calculation and application in SPSS package. L09: Cluster analysis. L10: Hierarchical clustering. L11: Nonhierarchical clustering methods and cluster analysis in SPSS. L12: Discriminant analysis. L13: Problems in applying of multivariate analysis. L14: Implementation of SPSS in multivariate data analysis. L15: Practical examples and case studies in the field of multivariate statistical analysis.


P01: Elements of matrix algebra. P02: Data types and measuring scales. P03: Parameters and scores of multidimensional distributions. P04: Multidimensional normal distribution. P05: Mean values tests. P06: Linear combinations of variables. P07: Using of SPSS software package. P08: Practical application of principal component analysis in SPSS. P09: Practical application of factor analysis in SPSS. P10: Practical application of hierarchical cluster in SPSS. P11: Practical application of nonhierarchical clustering in SPSS. P12: Practical application of discriminant analysis in SPSS. P13: Solving tasks in the field of multivariate analysis. P14: Review of different case study. P15: Workshop - practical work.

Literature/Readings

1. Kovacic Z., Multivariate analysis, Faculty of Economics, 1994. 2. Bulajic M, Jeremic V., Radojicic Z., advance fee manner given Multivariate hazards -

Contributions given to this Multivariate hazards, Faculty of Organizational Sciences, 2012. 3. Pallant J., SPSS Survival Manual - 4th edition, Allen & Unwin, 2011. 4. Radojicic Z., Linear statistical models, Faculty of Organizational Sciences, 2003.



Teaching methods

The traditional way of lecturing, with the use of whiteboard and computer.





Colloqia 20

Seminar work 20



Course:

Marketing

Teacher:Kostić-Stanković M. Milica,Janičić R. Radmila,Štavljanin B. Velimir,Damnjanović Ţ. Vesna,Cicvarić Kostić M. Slavica,Vlastelica Bakić L. Tamara,Vukmirović A. Jovanka


ECTS points: 5

Prerequisites: None

Course objective: To introduce students to the basics of market orientation of business and marketing instruments on which marketing is based, as well as the activities of marketing management.

Learning outcomes: Acquired basic knowledge, skills and abilities to perform market analysis, as well as to develop, implement and monitor the implementation of marketing strategies in domestic and international environment.

Course structure and content:

Theoretical study

market as a starting point for the implementation of marketing concepts. Target marketing. The system of interaction between the company and the environment. Macroenvironment and microenvironment of companies. The concept and importance of marketing. The development of the concept of marketing. The modern concept of marketing. Marketing information system. Marketing Research. Marketing mix. Product mix. Mix of prices. Mix of distribution and sales. Promotions mix. Marketing planning. Organization of marketing. Marketing control. International marketing.

Practical teaching: Practices, Other forms of lectures, Research work

Practices, Other forms of teaching, Research: Methodology of case studies. Market analysis, application of methods of internal and external analysis. Market segmentation, development of profiles of target segments and product positioning. Development of a plan for marketing research. Determination of product characteristics. The life cycle of the product. Methods of price determination. Development of distribution and sales strategy. Design of promotional activities. Analysis of various promotional campaigns. Marketing activities for services. Marketing plan. Development of marketing activities in the electronic environment. Development of marketing instruments for selected international environment.


Primary

Filipovic V, Kostic-M Stankovic, Marketing Management, Organizational Sciences, Belgrade, 2012.

Course materials and exercises

Additional litereature as required, in accordance with an agreement with subject teachers and associates


Lectures:

2

Labs:

2


Teaching methods

Lectures illustrated with additional audio-visual equipment, interactive discussions, small group work, problem and presentation of case studies, role-play, independent research by students and work through learning.



Participation in class 20 Colloquium 30



Degree level: I level – Basic Academic Studies

Course:

Mathematics 1

Teacher:Vujčić V. Vera,Stojanović A. Milica,Lazović P. Rade,Đorić S. Dragan,Mihić R. Olivera,Manojlović P. Vesna


ECTS points: 6

Prerequisites:-

Course objective

Exploring and mastering the mathematical content designed for engineer’s profile, related to the concept of number, basic concepts of algebraic structures, elements of linear algebra and analytic geometry, as well as the differential calculus of functions of one real variable.

Learning outcomes

Students are trained to use matrices and differential calculus of functions of one variable which belong to the class of basic tools for modeling organizational and technical systems.



1. Introductory concepts. 2. Algebraic structures. 3. Concept of a function. 4. Concept of a vector. Vector space. 5. Notion of a matrix. Operations with matrices. Rank of a matrix. Inverse of a matrix. 6. Systems of linear algebraic equations. Kronecker-Capelli theorem and Kramer theorem. Gauss algorithm. 7. The equations of the plane and of the line in the space. 8. Concept of real functions of one real variable. Sequences. Convergence criteria. 9. Limit of the function. 10. Continuity of the function. Properties of continuous functions on the segment. 11. First derivative of the function. 12. Differential of the function and its application. Differentials of higher order. 13. Basic theorems of differential calculus. Taylor formula. 14. Notion of an extreme. Necessary and sufficient conditions for the extreme. 15. Convex curves and inflection points. Curve asymptote.


Solving exercises from: 1.Binary relations and operations. 2. Group, ring, field. 3 Examples of functions. 4. Vector spaces. Scalar, vector and triple vector product. 5. Matrix multiplication, inverse matrix, rank of the matrix, eigenvalues and eigenvectors. 6 Solving systems of linear algebraic equations. 7. Line and plane. 8. Limit of the sequence. 9. Limit of the function. 10 Continuity of the function. 11. Derivatives of the function. 12. l’Hospital theorem. 13. Teylor formula. 14. Graph of the function. 15. Exam exercises.

Literature/Readings

1. D. Đorić, R. Lazović, Mathematics 1, FON, Belgrade, 2012. 2. O. Mihić., V. Baltić, M. Boriĉić, Methodical collection of solved problems in Mathematics 1, FON,

Belgrade, 2013



Teaching methods

Classical ex-cathedra teaching using blackboard and computer presentations




Colloquium 20 Oral exam 50

Seminars/homeworks 5


Degree level: Level I – Basic Academic Studies

Course:

Mathematics 2



ECTS points: 6

Prerequisites: -

Course objective

Mastering mathematical contents designed for the engineer’s profile, related to the differential calculus of functions of several variables and integral calculus of functions of one and several variables.

Learning outcomes

Students are trained to use differential calculus of functions of several variables and integral calculus of functions of one and several variables, which are the basic tools of organizational and technical system modelling.



1. Concept of a function of several variables. Limit value and continuity 2. Partial derivatives. Total differentials. Differentiability. 3. The existence of implicit functions. 4. Elements of field theory. Derivative in a given direction and gradient. 5. Taylor formula. 6. Necessary and sufficient conditions for constrained extremum. 7. Necessary and sufficient conditions for constrained extremum. 8. The definite integral. 9. The indefinite integral. Relation between definite and indefinite integrals. 10. Change of variables and partial integration. 11. Integration of rational and some irrational classes of functions. 12. Applications of integral calculus. Improper integrals. 13. Double and triple integrals. 14. Change of variables in double and triple integrals. 15. The infinite series. Power series.


Exercises from the topics: 1.Examples of functions of several variables. 2. Partial derivatives. 3. Derivatives of implicitly given functions. 4. Directional derivatives and gradient. 5. Taylor formula. 6. Problem of the unconstrained extremum. 7. Problem of contrained extremum. 8. Evaluation of definite integrals. 9. Methods of integration. 10. Integration of rational and some irrational classes of functions. 11. Applications of integral calculus. 12. Double and triple integrals. 13. Change of variables. 14. Convergence of the series.

Literature/Readings

1. M. Stojanović, O. Mihić, Matematika 2, FON, Beograd, 2013 2. S. Dajović, Matematika 2, FON, Beograd, 2007 3. Đ.Jovanov, R. Lazović, D. Đorić, Matematika 2, Workbook and Tests Examples, FON, 2009


Lectures:2 Labs:3 Workshops Research study

Teaching methods

The classic way of using the table, foils and presentation on computer.


Pre-exam requirements Points 30 Final exam Points 70


Participation in labs Oral exam 50

Colloquium 20

Seminars



Course:

Mathematics 3



ECTS points: 6


Course objective

The course focuses on the theory of ordinary differential equations and systems of differential equations. It includes selected topics from the calculus of one complex variable and Laplace transforms, with application of Laplace transforms to linear differential equations and systems of linear differential equations with constant coefficients.

Learning outcomes

Students are trained to analyze and solve simple classes of differential equations and systems of differential equations, including linear equations and systems. Students aquire basic knowledge of complex functions, analyticity, contour integration, residues and evaluation of integrals. Students are trained to apply Laplace transforms to linear differential equations and systems of linear differential equations.



1. Notion of a differential equation (DE). Existence and uniqueness of solutions to DE’s. 2. Examples of simple classes of first order DE’s and the corresponding solution methods. 3. Linear DE’s of second order. 4. Linear DE’s of order n. 5. Systems of DE’s. First integral. 6. Systems of linear DE’s. Fundamental matrix. 7. Matrix exponent. Stability. 8. Linear and quasi-linear partial differential equations of the first order. 9-10. Notion of a function of one complex variable. Analyticity. Cauchy-Riemann conditions. 11. Contour integral. Cauchy’s theorem and Cauchy’s formulas. Residues. 12. Evaluation of integrals. 13. Laplace transforms and basic properties. 14. Inverse Laplace transforms. Mellin’s formula. 15. Application of Laplace transform to linear differential equations and systems of linear differential equations with constant coefficients.


Solving exercises from: 1.- 2. Selected classes of first order DS’s. 3. Homogeneous linear DE’s with constant coefficients. 4. Variation of parameters method for non-homogeneous linear DE’s. 5. Systems of DE’s. 6. Systems of homogeneous linear DE’s with constant coefficients. 7. Variation of parameters method for non- homogeneous linear systems. 8. Partial DE’s of the first order. 9-10. Elementary functions of one complex variable. Constructing analytic functions using Cauchy-Riemann conditions. 11. Contour integrals. Residues. 12. Evaluation of integrals. 13. Laplace transform. 14. Inverse Laplace transform. 15. Applications of Laplace transform.

Literature/Readings

1. V. Vujĉić, S. Dajović, Mathematics 3, FON, Belgrade, 2009.

2. M. Stojanović, D. Đorić, R. Lazović, Mathematics 3, Collection of Problems, FON, Belgrade, 2004.

3. D. Đorić, Mathematics 3, Solved Provlems, FON, Belgrade, 2009.

The number of class hours per week Other classes:1

Lectures:2 Labs: 2 Workshops: Research study:

Teaching methods

Classical ex-cathedra teaching using blackboard and computer presentations


Pre-exam requirements Points: 30 Final exam Points:70

Participation in class 5 written exam 20

Participation in labs oral exam 50

colloquium 20 ..........

seminars/homeworks 5


Degree level: Level I - Undergraduate Studies

Course:

Mathematics and music

Teacher:Manojlović P. Vesna


ECTS points: 6

Prerequisites: none

Course objective

Connections between music and mathematics defined and established during centuries. Properties of numbers assist the development of the culture of the music in various ways. This program provides a foundation in mathematical structures and techniques required to study a range of musical domain.

Learning outcomes

To awaken in students an interest in the general science of harmony, whose mission is to explore new links between science and art, especially mathematics and music.


Theoretical course:

Math and music together through history,

Number and tone

Math, Music and spirals, logarithmic spiral,

The theory of rhythm

The use of logarithms in music

History tonal scale

Fourier analysis of the aliquot tones

The universal law of octave

Plato's body and music

Building musical accords

Musical interpretation of complex numbers

Golden proportion and golden scale

Fibonacci numbers

Research/Tasks in the field: A study of basic musical concepts in the light of the mathematical theory of music-student’s master in the study of musical accords and harmonies based on mathematical laws and rules


Lectures:

2

Labs:

2


Teaching methods







Degree level: undergraduate

Course:

Mathematical Logic with Applications

Teacher:Manojlović P. Vesna


ECTS points: 5

Prerequisites: Mathematics 1, Mathematics 2

Course objective

Acquire knowledge on general and special methods of formal logical reasoning, and main elements of the founding the scientific theory: consistency, independency, decidability, soundness and completeness.

Learning outcomes

Students will learn techniques of proving and refuting hypotheses, as well as skills of recognizing an incorrect logical reasoning, based on classical propositional and first-order predicate logic.



Axiomatic method and the deduction relation. Axiom independence. Consistency of a theory. Classical propositional and predicate logic – formal systems and models. Criticism of the classical two-valued logic and the paradoxes of implication. Many-valued logics. Proving and refuting - model and counter- model. Boolean algebras. Consistency, soundness, completeness and decidability of a logical system. The notion of a mathematical theory.


The topics covered by practical instructions and exercises match the theoretical topics given above.

Literature/Readings

1. J. Bell, M. Machover, A Course in Mathematical Logic, North-Holland, Amsterdam, 1977. 2. D. Bonevac, Deduction, Blackwell Publishing, Malden, 2003. 3. I. Lakatos, Proofs and Refutations, The British Journal for the Philosophy of Science XIV (1963), pp. 1-25, 120-139, 221-245, 296-342. (Prevod: Školska knjiga, Zagreb, 1991.)


– Lectures:

2

Labs:

2


–

Teaching methods



Pre-exam requirements Points 50 Final exam Points 50

Participation in class 15 written exam 25

Participation in labs oral exam 25

Project 35



Course:

Mathematical Models of Efficiency

Teacher:Martić M. Milan,Savić I. Gordana


ECTS points: 5

Prerequisites: None

Course objective

Introduction of the basic concepts of mathematical programming method – Data Envelopment Analyses (DEA), which is used for evaluating the performance of units that use multiple inputs to produce multiple outputs. The application procedure, the basic mathematical models and wel-know application is studied in detail.

Learning outcomes

Students will be able to independently apply data envelopment analysis and specialized DEA software packages for performance evaluation of profit and nonprofit units affected by diverse factors.



Measures and methods of performance measurement. Comparative Performance Analysis. Quantitative models for performance evaluation. Data Envelopment Analysis – DEA. Basic DEA models. Modified DEA models. DEA model to ranking of the efficient units. Procedure of DEA method application. Software for DEA. Comparison of DEA and regression analysis. Comparison of DEA methods and the multi-criteria analysis , Applications in banking sector. Applications in Health Care. Applications in Education. Other applications.


Definition of performance measures. The procedure for defining performance measures and analysis of raw data. The basic DEA models. Input and output -oriented DEA models - graphical presentation. The basic CCR model and BCC model. Weight restrictions. Limitation of DEA models. Target inputs and outputs. DEA model to ranking of the efficient units. Cross- efficiency matrix. Creating a model in spreadsheet environment - a case study. Software EDEA. Examples of applications in banking, healthcare, education, economic units’ efficiency evaluation.

Literature/Readings

Cooper W, Seiford L, Tone K, "Introduction to Data Envelopment Analysis and its Applications, With

DEA-Solver Software“, Springer, 2006,

Zue J, " Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets - Applications and implementations issues “, Springer, 2009.



Teaching methods

Lectures are followed by the corresponding presentations; all models will be illustrated on the hypothetical examples. Students will, through case studies, analyze the input and output factors that affect the efficiency, the results and use them to enhance the observed unit. The exercises are based on the use of MS Excel for practicing basic DEA models and software EMS and EDEA, DEA solver software for real problems




Participation in labs 10 Study 50


Degree level: : Undergraduate studies

Course:

Mathematical Software Packages

Teacher:Lazović P. Rade,Đorić S. Dragan


ECTS points: 6

Prerequisites: none

Course objective

To introduce students to the contemporary mathematical software packages.

Learning outcomes

Students are fully-fledged to use one of the contemporary mathematical software packages (MATLAB) and introduced to the basics of some others (MAPLE, MATHEMATICA)



Starting with MATLAB. Scalar variables in MATLAB. Elementary functions and terms. Mathematical operations with arrays. Matrices and matrix operations in MATLAB. Usage arrays. Scripting in MATLAB. Functions in MATLAB. User-defined functions. Relational and logic operators. Symbolic objects and terms. MATLAB graphics. Two-dimensional plots. Three-dimensional plots. Programming in MATLAB. Some pitfalls in MATLAB. Introduction to the software package MAPLE. Introduction to the software package MATHEMATICA.


Implementation numerical method in MATLAB. Using mathematical software packages in solving practical problems. Visualization in MATLAB.

Literature/Readings

1. A. Gilat, Uvod u MATLAB7 sa primerima, Mikro knjiga, 2005.

2. R. Maeder, Programming in Mathematica, Addison - Wesley, Reading, MA, 1996.

3. P. Stanimirovic, G. Milovanovic, Programski paket Mathematica i primene, Elektornski fakultet, Niš, 2002.

4. J. Penny, G. Lindfield, Numerical Methods Using MATLAB, Prentice Hall, 1995.


Lectures:

2

Labs:

2


Teaching methods

The classical methods using table, computer and projector.







Course:

Machine learning

Teacher:Delibašić V. Boris,Suknović M. Milija

Course status: Optional

ECTS points: 4

Prerequisites:

Course objective

Introduction to machine learning algorithms and selected software tools for their implementation.

Learning outcomes

Students have acquired the knowledge and skills to implement machine learning algorithms within the selected software environment.



1. Introduction; 2. Decision trees and association rules; 3. Linear regression; 4. Multiple linear regression. 5. Introduction to software tools; 6. Logistic regression; 7. Artificial neural networks – intro; 8. Artificial neural networks – continued; 9. Design of machine learning systems; 10. Support vector machines; 11. Clustering; 12. Dimensionality reduction and anomaly detection; 13. Recommendation systems. (Also included are two weeks of exams (mid and final exam).


Lab exercises are supporting the lecture topics through practical examples using selected software tools.

Literature/Readings

1. Delibašić B, Suknović M, Jovanović M (2009) Machine learning algorithms for data mining, FON (in Serbian)

2. Materials from webpage: https://www.coursera.org/course/ml The number of class hours per week Other classes:

Lectures:

2

Labs:

2


Teaching methods

Classical lecture, lab exercises, case study problems (benchmark problems, competitions data, real-world data)



Participation in class Project work 80

Participation in labs Written exam 20



Course:

Soft computing

Teacher:Vujošević B. Mirko,Makajić-Nikolić D. Dragana,Savić I. Gordana


ECTS points: 5

Prerequisites: Operations research 1

Course objective: to introduce students to contemporary soft computing approaches, primarily to solve problems of optimal decision making

Learning outcomes

Students will get insight into application of approaches based on fuzzy sets and logic to solving optimization problems in different areas and to use adequate software tools.


Both, theoretical and practical instruction: Approaches to modeling uncertainty, vagueness and imprecision. Management problems in terms of vagueness. Fuzzy sets and fuzzy logic. Probability and possibility measures. Fuzzy mathematical programming. Fuzzy linear programming. Decision-making systems based on fuzzy rules. Neural networks. The problems of classification and prediction. Fuzzy- neural systems. Evolutionary computing. Genetic algorithms. The ant algorithms

Literature/Readings : 1. M. Vujošević, Operaciona istraţivanja – izabrana poglavlja, FON, Beograd, 1999. 2. R. Hecht-Nielsen, Neurocomputing,Addison-Wesley, New York, 1990 3. G. Deco, D. Obradovic, An information-theoretic approach to neural computing, Springer Verlag,

Berlin, 1996. 4. G. J. Klir, B. Yuan, Fuzzy sets and fuzzy logic – theory and applications, Prentice Hall, Upper saddle

River, 1995 5. Xiang-Sun Zhang, Neural Networks in Optimization, Kluwer Academic Publishers, London, 2000


Lectures:

30

Labs:

30


Teaching methods

Theoretical instruction – interactive ex cathedra. Practical instruction – individual work with teacher’s assistance in computer room.



Participation in class 20 Oral exam from selected chapters 20


Homework 30

Alternatively

Written exam 60 Oral exam 40



Course:

Management

Teacher:Petrović Č. Dejan,Mihić M. Marko,Obradović LJ. Vladimir


ECTS points: 6

Prerequisites: /

Course objective

• Acquisition of the latest knowledge in the field of management, modern scientific discipline that deals with the problems of managing organizational systems.

• Understanding and mastering the latest methods and techniques that are used in management.

Learning outcomes

Students’ ability for implementation of professional knowledge, modern methods and techniques in the processes of planning, organizing, leading and monitoring of different activities, projects and organizational systems.



Definition and management development. Management processes. Functional areas of management. Planning process. The process of organization. Process of managing personnel. The process of leadership. The control process. Decision-making process. Information system for the management of the company. Manager. Manager and team work. Management and specialized management discipline. Management skills.


Methods and techniques of management. Planning methods. Methods of organization. Control methods. Managerial decisions. The knowledge and skills of managers. The selection and the choice of managers. The team formation. Case studies.

Literature/Readings

• Chuck W., Principles of Management, Data Status, Belgrade 2013

• Jovanovic P, Management - Theory and Practice, College of Project Management, Belgrade, 2007

• Robbins S.P, Coutler M, Management, Data Status, Belgrade 2005


Lectures:

2

Labs:

2


Teaching methods

Auditory, Illustrative and Demonstrative, Verbal and Textual, Practical Methods




Test/s 50




Course:

Human resource management

Teacher: Orlic D. Ranko


ECTS points: 5

Prerequisites: /

Course objective

Teaching students the basic concepts of human resources management, mainly focusing on various HRM activities including job analysis, job design, staffing (planning, recruitment, selection), performance appraisal, compensations and benefits, HR information systems, employee health and safety, equal employment opportunities, industrial relations etc.

Learning outcomes

This course qualifies students for: - Thorough comprehension and understanding of different HRM activities, policies and practices - Analysis and implementation of HRM activities - The ablility to solve HR-related issues using specific methods and procedures taught within the course - Combining knowledge acquired in different fields during the course of studies and the practical application of said knowledge - Applying up to date information and the latest IT solutions in implementing various HRM practices



Course introduction: basic terms and jobs in HRM; Ensuring equal employment opportunities; Designing jobs and work tasks; Analyzing jobs and work tasks; Human resource planning and recruitment; Selection; Orientation and training; Human resource development and career planning; Performance management; Compensations; Employee health and safety; Coordination; Research in human resources and HRM information system; Trade unions and collective bargaining; Future of human resource management.


Course introduction: basic terms and jobs in HRM; Ensuring equal employment opportunities; Employee health and safety; Analyzing jobs and work tasks; Designing jobs and work tasks; Human resource planning; Recruitment; Selection; Revision; Orientation and training; Human resource development and career planning; Performance management; Compensations: Pay and rewards; Compensations: Benefits; Trade unions and collective bargaining; Revision.

Literature/Readings

1. R. Orlic, Kadrovski menadzment, Zoran Damnjanovic i sinovi, Beograd, 2005.



Teaching methods

Lectures, interactive classes: workshops, exchanging ideas and knowledge through group discussion, learning by example using case studies, mentoring and teamwork aimed at preparing essays on agreed topic, presentation method.



Participation in exercises 10 Written exam 30

Tests 40

Essay(s), homework assignment(s)

20



Course:

Management of technology and development

Teacher:Levi-Jakšić I. Maja,Marinković P. Sanja

Course status: Obligatory

ECTS points: 5

Prerequisites: /

Course objective:

Providing knowledge and skills of strategic and operational technology management. Students gain insights in the practices and cases related to solving specific issues of forecasting, planning, organizing and managing the dynamics of change of technology, technological systems, processes and operations in compаnies.

Learning outcomes: Students are equipped with knowledge and skills of strategic and operational technology management in the areas of forecasting, planning, organising and managing the dynamics of change of technologies, technology systems, processes and operations. The students gain team work experience by fulfilling assignments of problem analysis and critical thinking based on innovative companies examples. The students are introduced to software applications used in solving concrete problems and tasks in Course structure and content

Theoretical instruction: Management of Technology; Technology and organization; Integrative models of organization; Strategic management of technology; Support for the strategic management of technology; Operational management of technology; Support for the operational management of technology; Components of processes and operations; The output of the technological system; Technology transfer; Globalization and technological cooperation; Global technology strategies.

Practical instruction: Analysis of examples of application and solving problems by using different methods in management of technology and development: Technological forecasting: Delphi, PATTERN, Brainstorming; Indicators of technology performance in the enterprise: Indicators of technological progress (TP), TP types, TP rate, The matrix of objectives; Methods of evaluation and selection of technology: The Method of Ranking, AHP method, Methods for supporting technology innovation in the enterprise; Solving tasks by using the software, Application of methods in domestic enterprises; Creative workshops; Presentation of term papers and project assignments.


Burgelman, R, Christensen, C. M., Wheelwright, S. C., Strategic Management of Technology and Innovation, Mc Graw Hill, 2008.

Cetindamar, D., Phaal, R., Probert, D., Technology Management – Activities and Tools, Palgrave Macmillan, 2010.

Harrison, N., Samson, D., Technology Management - Text and International Cases, Mc Graw Hill, 2002.

Levi Jakšić, M., Menadţment tehnologije i razvoja, Ĉigoja štampa, Beograd, 2010

Levi Jakšić, M., Marinković, S., Petković, J., Menadţment inovacija i tehnološkog razvoja, FON, Beograd, 2011

Levi Jakšić, M., Marinković, S., Obradović, J., RS PC tehnologija, Edukativni softver, Beograd, 2005


Lectures: 2 Exercises: 2 Workshops: Research study:

Teaching methods: Lectures, interactive workshops, exchange of ideas and knowledge through group discussions, learning through the case studies, mentoring and teamwork; Power Point presentations with case studies; Training students to apply technology forecasting methods and techniques in companies; Solving tasks with active participation of students; Involving students in research work through seminar papers.



Colloquium: two 48 written examination - tasks (instead of seminar papers and workshop)

40

written examination - theory 12



Course:

Optimization Methods

Teacher:Vujošević B. Mirko,Stanojević J. Milan


ECTS points: 5

Prerequisites: Operations Research 1

Course objective

Students will get insight into application of optimization methods to decision making processes in different areas: Supply Chain Management, finding network topologies of computer, telecommunication and road networks, multi-criteria decision making, decision making under uncertainty and incomplete information.

Learning outcomes

With knowledge obtained at this course students will be able to understand role, importance and advantages of optimization in decision making process. They will be capable to apply optimization methods and techniques and to use actual software solutions for optimization-based decision support.


Both, theoretical and practical instruction: 1. Network optimization: Shortest path problem; problem of finding all shortest paths between all vertices in a network; shortest spanning tree, Steiner tree problem; travelling salesman problem; network flow problems. 2. Location problems: discrete location problems; continuous location problems; location-allocation problems; network location problems. 3. Multi-criteria optimization: basics; methods for determining efficient solutions (a priori approach); methods for determining entire set of efficient solutions (a posterior approach). 4. Identification and approximation problems and application of neural networks in their solving. 5. Basics of genetic algorithms. 6. Introduction to fuzzy sets and fuzzy linear programming.

Literature/Readings

1. M. Vujošević, M. Stanojević, N. Mladenović, Optimization Methods: Network, Location and Multi- criteria Models, ugoslav Operational Research Societ, 1996. (in Serbian)

2. D. Cvetković at al. Combinatorial optimization, Jugoslav Operational Research Society, Belgrade, 1997. (in Serbian)

3. M. Vujošević, Optimization methods in engineer management, Faculty of Organizational Sciences, Belgrade, 2012. (in Serbian)

4. R. Fourer, D.M. Gay, B.W. Kernighan, AMPL: A Modeling Language for Mathematical Programming, Duxbury Press / Brooks /Cole Publishing Company, 2002.

5. A. Makhorin, Modeling Language GNU MathProg Language Reference, Free Software Foundation,

2013.


Lectures:

30

Labs:

30


Teaching methods

Theoretical instruction – interactive ex cathedra. Practical instruction – individual work with teacher’s assistance in computer room. Also, can be realised as a block classes in the corresponding amount.



Participation in class 20 Oral exam from selected chapters 20


Homework 30

Alternatively

Written exam 60 Oral exam 40



Course:

Mobile business

Teacher:Radenković LJ. Boţidar,Despotović-Zrakić S. Marijana,Bogdanović M. Zorica,Barać M. Dušan,Krčo M. SrĎan,Vasković R. Vojkan


ECTS points: 5

Prerequisites:

Course objective

The aim of the course is to learn about mobile technologies in e-business. Students are enabled to independently design and implement mobile applications

Learning outcomes

Students gain theoretical and practical knowledge that are necessary for development and implementation of mobile business systems and applications.



Introduction. Wireless transmission techniques. Mobile and wireless networks. Design of wireless networks. Mobile operating systems. Development platforms and environments. Web services in a mobile environment. GPS technology and network services for positioning. Mobile identification technology. 2D barcode. RFID. NFC technologies. Personal Area Networks. Wireless sensor networks. Ubiquitous computing, Context-Aware systems. Security of mobile and wireless networks. Mobile business services. Designing mobile business applications


Development environment for the design of mobile applications. Essential concepts for the mobile applications development. Android Mobile Applications development. UI elements. Dynamic adaptability and internationalization of interfaces. Structure and communication between components of Android applications. Mechanisms for data persistence. Working with SQLite databases. Fragmentation, modularity and re-use of interfaces. Techniques for compressing information in a limited space. System events and notifications in Android. Using phone’s common functionalities. Use of location service in Android mobile application. Data transmission technology. XML and JSON formats for data. Development of iOS mobile applications. Development of Windows Phone mobile applications. Developing applications for SMS server.

Literature/Readings

1. E-resources from web site www.elab.rs 2. Despotović-Zrakić M., Milutinović V., Belić A. (Eds), High performance and cloud computing in

scientific research and education, monografija, IGI Global, 2014. 3. Professional Android Sensor Programming, Greg Milette, Adam Stroud, John Wiley & Sons, Inc.,

2012, ISBN 978-1-118-18348-9 4. R. Meier, Professional Android 4 Application Development, 2012, ISBN: 978-1118102275 The number of class hours per week Other classes:


Teaching methods





Project (mobile application) 40



Course:

Mobile computing

Teacher:Starčević B. Dušan,Minović V. Miroslav,Milovanović M. Miloš


ECTS points: 4

Prerequisites:

Course objective

Acquire knowledge and skills needed for programming applications for mobile devices in various system environments with limited system resources. Connecting mobile devices to mobile networks.

Learning outcomes

Students will acquire basic knowledge and skills needed for programming applications for mobile devices, enabling them to work as a mobile applications developer of native and hybrid applications for Android and iOS platform.



P-01: Introduction to mobile computing. P-02: Wireless communications. P-03: Standards in wireless networks. P- 04: Cellular Networks: Standards and Technology. P-05: Mobile operating systems. (Android) P-06: Mobile operating systems. (iOS) P-07: Mobile operating systems. (Windows Mobile) P-10: Mobile applications. (Android) P-11: Mobile applications. (iOS) P-12: Mobile applications. (Windows Mobile) P-13: The elements of computer graphics in mobile computing. (Android) P-14: The elements of computer graphics in mobile computing. (iOS) P-15: The elements of computer graphics in mobile computing. (Windows Mobile)


V- 01: Examples of mobile computing technology . V- 02: Work with the typical mobile devices and platforms. V- 03: Examples of the design and implementation of Wi - Fi networks . V- 04: Examples of work with Bluetooth V- 05: AndroidOS characteristics and work with development environments. V- 06: Workshop : Making AndroidOS applications . V-07 : Features of iOS and working with development environments. V- 08: Workshop : Creating iOS apps . V- 09 : Features of the Windows Mobile OS and working with development environments. V-10 : Workshop : Creating Windows Mobile OS applications . V-11 : The development of network applications with mobile services . V- 12: Application Development with sensor technologies . V- 13: Managing user interface. ( AndroidOS ) V-14 : Managing user interface. ( iOS) V-15 : Managing user interface . ( Windows Mobile OS)

Literature/Readings

1. J. McWherter, S. Gowell, Professional Mobile Application Development, Wrox, 2012 2. A.F. Molisch, Wireless Communications, Wiley, 2010 3. Kurose, Ros, Umrežavanje računara, CET, Beograd, 2009.



Teaching methods

Lectures, labs




Project 30



Course:

Business Process Modeling

Teacher:Nešković N. Siniša,Aničić M. Nenad


ECTS points: 5

Prerequisites: -

Course objective

To attain theoretical and practical knowledge needed in business process modeling as well as to learn basic techniques for an efficient process automation

Learning outcomes

Students will be enabled to analyze, identify and model business processes using appropriate formal methods and by using modern software tools to define their automation.



The concept of business processes (BP). Modeling organizational systems. Theoretical basis for BP modeling. Petri nests. State chart diagrams, Object life cycles. BPMN and UNL Activity diagrams. Basis of BP modeling methodology. Analysis of BP. Hierarchical decomposition. Specification of BP. Choreography and orchestration. Standards for BP modeling. UMM (UN/CEFACT Modeling Methodology) standard. Workflow management systems. Process based information systems. Service oriented architecture (SOA). BPEL and WSDL standards


Examples of BP. Relation to other management disciplines. Petri nets and UML State chart diagrams. UML Activity diagrams. BP Workflow patterns. BP analysis. BP specification. Choreography and orchestration. Standards for BP modeling. UMM views and models. Workflow management systems. BP metamodels. Workflow automation. SOA. BP management.

Literature/Readings

• Slajdovi sa predavanja u e-formi • Bruce Silver, BPMN Method & Style: A levels-based methodology BPM process modeling and

improvement using BPMN 2.0, second edition, Cody-Cassidy Press, 2009, ISBN: 978-0982368107 • Michael Havey, Essential Business Process Modeling, O'Reilly Media, 2005, ISBN: 978-0596008437 • UN/CEFACT Modeling Methodology (UMM) User Guide,

www.unece.org/cefact/umm/UMM_userguide_220606.pdf


0 Lectures:

2

Labs:

2

Workshops:

0

Research study:

0

Teaching methods

Conventional lecturing and exercises. Case studies. Seminar work in small groups.



Project 40 Written exam 40

Oral exam 20



Course:

Financial systems modeling

Teacher:Bogojević-Arsić T. Vesna,Petrović J. Bratislav


ECTS points: 4

Prerequisites:

Course objective The aim of this course is to provide students with the necessary theoretical knowledge of the fundamental concepts, methods and techniques for financial systems modeling and their application for solving practical financial problems.

Learning outcomes The acquired knowledge will enable students to appropriately model and simulate financial systems, to price financial instruments, and to build intelligent systems for forecasting and automated trading.



Introduction to financial systems modeling – mathematical basics. Financial markets, financial instruments, basic characteristics of financial markets. Preferences, Utility function. The concept of equilibrium, Equilibrium for single-agent financial market, Equilibrium for multi-agent financial market. Models for pricing financial instruments. Market impacts models. Time series models. Volatility models. Forecasting models. High frequency trading and Black-box model. Risk and risk analysis. Systems for risk analysis and control.


Practical instructions closely follow the lectures. In the course, students gain hands-on knowledge and skills for solving practical problems using selected software packages (Matlab, Mathematica and SciLab).

Literature/Readings

1) S. Benninga, Financial Modeling, MIT Press, 1997.

2) V. Bogojević-Arsić, Korporativne finansije, FON, 2006.

3) V. Bogojević-Arsić, Upravljanje finansijskim rizikom, FON, 2009.

4) S. Stojanović, Computational financial mathematics using Mathematica: optimal trading in stock and options, Birkhauser, 2003.



Teaching methods

Lectures. In the course students gain hands-on knowledge and skills for solving practical problems using selected software packages (Matlab, Mathematica and SciLab). Mentoring. Project assignments for individuals or small groups.







Course:

Multimedia production

Teacher:Starčević B. Dušan


ECTS points: 4

Prerequisites:

Course objective

Acquire knowledge and skills needed for work in multimedia production team. Understanding roles of producer, director and writer as a team manager.

Learning outcomes

Students will acquire basic knowledge and skills in the field of multimedia production, enabling them to produce multimedia projects with adequate methodological approach. Course structure and content


Multimedia industry . Market . Technology . P- 02: multimedia studio . Devices . Integration . Using. P - 03 : Interactive Design . The main roles . Producer . Director. Screenwriter . P- 04: Components of multimedia system . The design of multimedia systems for training and learning . Games design. P- 05: Fundamentals of production. Instructions . Characteristics . Genres . P- 06: The interactive design process . Design team . Writing concept. P- 07: Analysis of Competitiveness . Top -level design . Cost / benefit analysis . P- 08: Functional specification . P-09 : Overview of the development process. Clients . Stages of development . P- 10: The research phase . Client and implementer qualifications. Key points of the job . Determination of work items. Metrics. A preliminary implementation plan and budget. Suggestions and offer. Contract . P -11: the design phase . Design phase outputs . Graphics . (Display area . Icons . Font . Role. Casting . Scenario . Palette. ) P- 12 Sound . ( Casting. Music . Sound effects. ) Technical issues. ( Tools. technical parameters . Software and databases. ) The role of producer . The role of the director. The role of the writer . P -13: Prototype. The purpose of the prototype . Prototype planning and implementation. Testing the prototype . Using the test results . P -14 Production. Production outputs. Approval of production material. Tasks in stage productions. The roles of producer and director in the development stage . P-15 : alpha and beta discs . Gold master . Package design . Archiving .


V- 01: Introduction to multimedia production ( Introduction to the devices and tools ) V- 02: Establishment of project teams and defining project tasks V- 03: Workshop : Role play and team distribution to basic roles V- 04: Workshop: Generating ideas for production projects and defining the basic components of the system - the target group , content , interactive features , structures , controls , layout applications V- 05: the user interface. Generation of user interfaces . Designing the user interface . Examples of user interfaces of interactive applications . V- 06: Workshop: concepts and competitive analysis (development of a competitive matrix ) V- 07: Workshop: Top -level design and cost-benefit analysis V- 08: Workshop: Development of functional specification V- 09: Research . The research needs of the users of the production project. Planning a research meeting . The report analysis . The preliminary development plan . The preliminary budget . V - 10 : Design . Background design and display text . Icons design.

Design and development of character . Scenario . V-11 : Background music. Character and background speech recording. The choice of music. The choice of sound effects. Preparation of the final plan and final budget . V- 12: Prototype . Graphics . Video . Sound. V- 13: Production . V -14 testing . V-15 : Projects.

Literature/Readings

1. Starčević, D., Štavljanin, V., (2013), „Multimediji―, FON, Beograd 2. Elin, Larry, Designing and Developing Multimedia – A Practical Guide for the Producer, Director, and

Writer, Allyn & Bacon, MA, USA, 2001 The number of class hours per week Other classes:


Teaching methods

Lectures, labs, practical work, consultations




Project 20



Course:

Multimedia

Teacher:Starčević B. Dušan,Štavljanin B. Velimir


ECTS points: 4

Prerequisites:

Course objective

Enabling students to understand fundamental characteristics of multimedia objects and systems. Acquiring knowledge and skills in order to utilize tools and multimedia technologies in integration of multimedia objects with Web artifacts.

Learning outcomes

Students will acquire basic knowledge and skills needed for utilization of tools and multimedia technologies. This course will enable students to work with images, perform audio and video production or to create an website.



P- 01: Introduction to multimedia information systems . Definitions . Motivation and objectives . The evolution of multimedia. Areas of application . P- 02: Multimedia hardware technology . Platform. Peripherals . Interfaces . Storage devices and storage . Input devices . P- 03: Multimedia hardware technology . Output devices . Communications . Distributed multimedia systems . P- 04: Multimedia building blocks, techniques . Text and typography . Graphics . Sound. Image . Animation Video . P- 05: Compression standards 1 P- 06: Compression standards 2 P-07 : Design of multimedia information systems . Generic Multimedia information system Architecture. P-08 : Design of multimedia information systems . The data model of time -oriented media . P-09 : Design of multimedia information systems . Structured media objects . P -10 : Multimedia Database . Working with text . Working with pictures . P -11: Working with video. Search and retrieval in multimedia information systems . Implementation . P -12 multimedia software technology . Basic tools . Instant multimedia tools . P -13: Authoring Tools. P-14 : Multimedia and Internet . MIME. WWW. Hypertext . Hypermedia . P -15 Web page makers and editors . Plug - ins .


V- 01: Introduction to Multimedia ( media types , file formats , standards) V- 02: Web Technologies (overview of current technology , multi-layer architecture , HTML , scripting languages ) V- 03: Workshop : Dreamweaver (HTML , work with templates , behaviors , advanced techniques ) V- 04: The digital images (format, the basics of Photoshop , advanced options , filters) V- 05: Workshop : Photoshop ( layers , masks , channels , actions ) V- 06: Multimedia database (basic concepts , characteristics extraction, search ) V- 07: The digital video V- 08: Workshop : Premier ( MPEG -4 compression standard , Authoring ) V- 09: MIME. V- 10: The digital sound . V-11 : Workshop : Audition V- 12: WWW. Hypertext . Hypermedia V-13 : Workshop : Dreamweaver (HTML , CSS) V -14 Multimedia Programming V-15 : Workshop : Adobe AIR, Adobe Flex .

Literature/Readings

1. Starčević, D., Štavljanin, V., (2013), „Multimediji―, FON, Beograd 2. Havaldar, P., Medioni, G. (2010), Multimedia Systems: Algorithms, Standards, and Industry Practices,

Boston, MA: Course Technology, Cengage Learning The number of class hours per week Other classes:


Teaching methods

Lectures, labs




Project 20



Course:

Advanced .NET technologies

Teacher:Lazarević D. Saša


ECTS points: 4

Prerequisites: Non

Course objective: Understanding of .NET platform’s advanced concepts and technologies based on them. Software implementation by using advanced .NET concepts. Mastering the various implementing models and technologies. Application of appropriate software tools for software construction based on.NET platform technologies.

Learning outcomes: Competence of students to develop software using advanced .NET technology.

Course structure and content (Syllabus):

Lectures:

1. Introduction: objectives, methodological units, mode, method of examinations, literature, teachers and staff. Basic concepts. NET platform: properties, parts, architecture.

2. Exceptions and exception handling, User-defined conversion, Delegates, Events, preprocessor directives, Attributes, Memory management, Unsafe code.

3. Reflection, Collections, Threads, Templates and Generics.

4. Assemblies, adding resources within the global assembly cache, the configuration of components.

5. XML programming, XML standards, XPath, XSLT, XML and ADO.NET, XML serialization.

6. Working with Files, the Registry, and Active Directory.

7. Implementation of Web applications: ASP.NET and ASP.NET MVC.

8. The design of distributed applications: XML Web Services, NET Remoting and WCF.

9. Implementation of the Windows service. Implementing security in .NET.

10. Presentation Layer: WPF.

11. Windows Workflow Foundation, WWF.

12. Data-oriented applications: ADO.NET and ADO.NET Entity Framework, LINQ.

Labs: The order of labs exercises and labs exercise content is fully compliant with lecturing units.


1. C. Thilmany: .NET Patterns: Architecture, Design and Process, Addison-Wesley, 2006.

2. A. Troelsen: Pro C# 2013 and the .NET 4.5 Platform, APress, Berkeley, 2013. 3. S. Wiltamuth, A. Hejlsberg: C# Language Specification, msdn.microsoft.com 4. S. Stiefel, L. Oberg: App Development using C# and .NET, Prentice Hall PTR, 2013. 5. S. Robinson, et al.: Professional C# Programming, Wrox Press, 2012. 6. S. McConnell: Code Complete: A Practical Handbook of Software Construction, Microsoft Press, 2004. 7. B. Wagner: Effective C#, Addison-Wesley, 2004. 8. S. J. Metseker: Design Patterns in C#, Addison-Wesley, 2004.


/ Lectures: 2 Labs: 2 Workshops: / Research study: /

Teaching methods: Lectures: Lectures ex cathedra, and with the use of multimedia resources; explanation of the case study. Labs: case studies, programming.




Project (required) 30 Oral exam 20



Course:

Advanced Java Technology

Teacher:Vlajić S. Siniša

Course status: Election

ECTS points: 4

Prerequisites: -

Course objective: Gaining knowledge of the advanced Java technologies used in the development of complex (enterprise) applications. Creation of the complex Java applications using Java Web, EJB and XML technologies.

Learning outcomes: Ability of students to design and implement complex applications using J2EE technologies.



Java Web technologies: Java servlets, JSP (JavaServer Pages), ..., JSF (JavaServer Faces).

Java EJB technology: Session beans, Entity beans, Message Driven Beans.

Java XML technologies: JAXP (the Java API for XML processing), JAX-RPC (the Java API for XML based RPC), SAAJ (SOAP with Atachments API for Java), JAXR (the Java API forXML Registries).

Java technology to work with the database: Hibernate, ..., Torgue.


Java servlets, JSP, JSF, Session beans, Entity beans, JAXP, JAXR, Hibernate.

Literature/Readings

Basic literature:

1. Siniša Vlajić, Dušan Savić, Vojislav Stanojević, Ilija Antović, Miloš Milić: Software design – advanced software technologies, Zlatni presek, (on serbian language) ISBN: 978-86-86887-03-0, Belgrade, 2008. 2. Siniša Vlajić, Dušan Savić, Vojislav Stanojević, Ilija Antović, Miloš Milić: Advanced software technologies, book in preparation, 2013. Additional literature:

1. Monica Pawlan , Java 2 Enterprise, Edition Technology Center, March 23, 2001

http://java.sun.com/developer/technicalArticles/J2EE/Intro/ 2. The J2EE 1.4 Tutorial, Sun Microsystems, August 31, 2004



Teaching methods

• The professor will theoretically explain each of the considered thematic units and by practical examples will explain their use in the development of complex software systems.

• Assistants will elaborate thematic units which professor explained. For each thematic unit assistants will prepare concrete examples that will show and explain to the students in the computer center.

• Students should to do tasks, which will be prepared by assistants.



Seminar 20 Exam on the computers 80



Course:

Numerical Analysis

Teacher:Lazović P. Rade


ECTS points: 6

Prerequisites: Mathematics 1, Mathematics 2, Mathematics 3

Course objective

Introduction of the basic numerical methods and corresponding mathematical software.

Learning outcomes

Students will be able to applay different numerical methods and specialized numerical software in solving practical problems.



Approximate numbers. Kinds of errors. Errors of approximate value of functions. Inverse problems. Solving nonlinear equations. Bisection method. Newton's method. Regula falsi method. Fix point theorems. Iterative method. Vector and matrix norms. Iterative methods for solving systems of linear equations. Method Jacobi. Gauss-Saidel's method. Solving systems of nonlinear equations. Iterative method for nonlinear systems. Newton's method. Interpolation. Interpolating polynomials. Lagrange polynomials. Newton's polynomials. Spline interpolation. Least-squares approximations. Numerical differentiation and integration. Rectangle, trapezoidal and simpson's rules. Gaussian quadrature. Numerical solution of ordinary differential equations. Euler's method and its modifications. Runge-Kutta methods.


Implementation of the numerical methods in the software package MATLAB. Exercises. Applied problems and projects.

Literature/Readings

1. Rade P. Lazović, Numerical methods, FOS, Belgrade, 2013.

2. Rade P. Lazović, Numerical analysis, theory review, examples, problems, FOS, Belgrade, 2009.

3. C. F. Gerald, P. O. Wheatley, Applied Numerical Analysis, California Polytechnic State University, 2004.

4. D.Faires, R.Burden, Numerical Methods, Thomson, 2003.

5. A.Quarteroni, R.Sacco, F.Saleri, Numerical mathematics, Springer, 2007.


Lectures:

2

Labs:

2

Workshops:

1

Research study:

Teaching methods

All the lectures are followed by corresponding presentations. The labs exercises are based on the use of mathematical software EASY NUMERICS and implementations in software package MATLAB.




Participation in labs 40 Study 20



Course:

Selected Topics in Information Systems

Teacher:Marjanović M. Zoran,Nešković N. Siniša,Vučković Đ. Milica,Aničić M. Nenad,Babarogić S. SlaĎan,Pantelić S. Ognjen



Prerequisites: /

Course objective

The goal of this course is to train students to independently research aspects of selected topic and apply gained knowledge in practice.

Learning outcomes

Students will gain detailed insight in achievements in subject area of selected topics. Also, student will learn methodology and evolve necessary skills which help him in gaining knowledge in any other scope inside information systems area.


Practical instruction: Student projects under mentor supervision

Seminar topics approval 1. Seminar topics approval 2. Project consultation 1. Project consultation 2. Final achievements analysis.

Literature/Readings

1. Literature available online


Lectures: Labs: Workshops: 1 Research study:

Teaching methods

Lectures (30 classes), labs (30 classes) and practical labs (30 classes). Case studies.



Seminar 70 Seminar presentation 30



Course:

Operations research 1

Teacher:Vujošević B. Mirko,Čangalović M. Mirjana,Martić M. Milan,Stanojević J. Milan,Kuzmanović S. Marija,Savić I. Gordana,Makajić-Nikolić D. Dragana

Course status: Mandatory

ECTS points: 6

Prerequisites: Mathematics 1, Mathematics 2

Course objective: Instructing students to basic concepts and methods of operations research (linear, nonlinear and integer programming). The stress will be on modelling as one of basic methods of management science.

Learning outcomes: Content of this course qualifies students for mathematical modelling of business and organizational systems and solving the practical management problems applying quantitative methods using modern software tools.


Theoretical instruction: Introduction to Operations Research (OR) and mathematical programming: methodology of OR, mathematical model, feasible solution, optimal solution, local and global optimum. Linear programming (LP) and its characteristics. Geometric interpretation of LP. General, symmetric, standard and canonical form of LP problem. Simplex method. Possible outcomes of simplex method. The dual LP problem, its features and application possibilities. Transportation problem (TP). Some special cases of TP. Standard combinatorial optimization problems (assignment problem, knapsack problem, etc.) and their solving by exact and approximate methods. Integer programming and its solving methods. The basic characteristics and properties of non-linear programming problem (NP). The use of LP and NP in business analytics.

Practical instruction: Basic concepts of mathematical modelling. Modelling of standard problems in management (portfolio optimization, diet problem ...). The formation of some specific mathematical LP models. Graphical method of solving LP problems. Simplex method – the basic steps. Simplex Method – advanced techniques. The transport problem: modelling and obtaining the initial solution. Methods for solving TP to optimality. Specific application of TP in management. Solving some standard problems of combinatorial optimization using exact and approximate methods. Optimization problems on networks. Exact methods for solving integer programming (branch and bound). Nonlinear programming (NP): formulation of NP models, solving NP problems using analytical and numerical methods.

Literature/Readings

Basic:

1. S. Krĉevinac at al., Operations Research 1, FOS, Belgrade, 2013. (in Serbian)

2. M. Martić at al., Operations Research 1 – Selected Sasks, FOS, Belgrade, 2013. (in Serbian)

Additional:

1. M. Vujošević, Linear programming, FOS, Belgrade, 2013. (in Serbian)

2. J.A. Lawrence, B.A. Pasternack, Applied Management Science, John Wiley & Sons Inc. 2002.


Lectures:

30

Labs:

30

Practical work:

15

Research study:

seminar task

Teaching methods: Classic (ex cathedra) using blackboard, computer, projector. Solving short case studies and practical work in computer room.



Colloquium – tasks 40 Written exam (alt. to coll. tasks) 40


Colloquium – theory 40 Oral exam (alt. to coll. theory) 40

Seminar tasks 15



Course:

Operational Research 2

Teacher:Vujošević B. Mirko,Čangalović M. Mirjana,Martić M. Milan,Stanojević J. Milan,Kuzmanović S. Marija,Savić I. Gordana,Makajić-Nikolić D. Dragana


ECTS points: 5

Prerequisites: Mathematics 1, Mathematics 2, Theory of probability

Course objective

The objective is to enable students to understand different methods and techniques of operations research which can be applied in the various fields of management. Stress will be on project planning techniques, network optimization, dynamic optimization, game theory, heuristics, queuing and inventory optimization models.

Learning outcomes

Students will gain the knowledge in quantitative methods which represent the compulsory fund of knowledge for modern engineers and managers. Students will be able to understand, analyze and model practical problems in the various fields of management. They also will be able to solve problems by applying quantitative methods using modern software tools and present results in a proper form for decision making.


Theoretical and practical instructions covering the following areas: Project Planning, Analysis of the structure. Network Planning - CPM and PERT. Planning of the project cost by PERT - cost and LP methods. Game Theory - Introduction, simple and mixed matrix game, domination of strategies. Solving mixed matrix games. Determination of equilibrium and optimal strategies in bi-matrix games. Heuristic methods - principles, classification and application. Models of multi-stage decision making, dynamic programming - recurrence relations. Solving multi-phase management process by dynamic programming. Analysis of the queuing systems. Modeling systems with queues - Markov chains. Deterministic models of inventory management. Stochastic models of inventory management. Reliability optimization.

Literature/Readings

J.A. Lawrence, B.A. Pasternack, Applied Management Science, John Wiley & Sons Inc. 2002.


Lectures: 2 Excursuses: 2 Workshops: Research study:

Teaching methods

The classical way (ex-cathedra) using table, computer, projector, resolution of short case studies and one

hour of labs weekly.



Participation in class 5 Oral exam (alt to midterm test) 40

Project study 15 Written exam (alt to midterm test) 40

Midterm tests (theoretical and practical part) 80



Course:

Optimization in Natural Resources Management

Teacher:Stanojević J. Milan,Petrović B. Nataša


ECTS points: 5

Prerequisites: Operations research 1, Operations research 2

Course objective

Introducing basic concepts of natural resources management to students. Identifying problems in the usage of different types of natural resources and their renewal. Solving these problems with methods and techniques of operations research.

Learning outcomes

Knowledge of solving optimization problems in the use of natural resources, as well as adequate interpretation of the results. Skills for application of operations research and mathematical techniques: linear, integer and multi objective programming, stochastic and combinatorial optimization.



Analysis of natural resources in the world with special focus on Serbia – agro-industry, forestry, fishing and mining. Specifics related to the time horizon; special reference to analysis of risk and uncertainty. Review of applications of operations research in natural resources industry. Modelling of selected problems in the agro-industry, forestry, fisheries and mining. Solving selected optimization problems with methods of linear, nonlinear and integer programming using available software. Positive Mathematical Programming.


The practical instruction is designed to follow the theoretical classes. Units are covered with available software tools applied to actual real world examples.

Literature/Readings 1. Handbook of operations research in natural resources, editors Andres Weintraub, Carlos Romero,

Trond Bjørndal, Rafael Epstein, Published by Springer Science+Business Media, LLC, 2007. 2. A Long View of Research and Practice in Operations Research and Management Science: The Past

and the Future, editors ManMohan S. Sodhi, Christopher S. Tang, published by Springer Science+Business Media, LLC, 2010.

3. S. Krĉevinac et al., Operations research 1, Faculty of Organizational Sciences, Belgrade, 2013. (in Serbian)

4. S. Krĉevinac et al., Operations research 2, Faculty of Organizational Sciences, Belgrade, 2013. (in Serbian)


Lectures:

2

Labs:

2


1

Teaching methods

The course is performed using ex-cathedra, lectures, research seminars, practical classes, fieldwork and team work and independent research. All members of the class are expected to show genuine commitment to maximize the return from the time invested in the class. There will also be a number of practical exercises and problems to be solved in the classroom or at home.




Homework 20 Seminar work 40



Course:

Fundamentals of Information and Communication Technologies

Teacher:Simić B. Dejan,Milovanović M. Miloš


ECTS points: 5

Prerequisites:

Course objective

Students are introduced to basic concepts in information and communication technologies and acquire the necessary skills to work on a computer. This will significantly improve their productivity in solving problems with the help of information technology and tools typically available on a personal computer.

Learning outcomes Students will gain the knowledge and skills needed for work on a computer, as well as fundamental knowledge required for the analysis and application of modern information and communication technologies.



L-01: Number Systems and Codes, L-02: History of Computing, L-03: Data, information, and knowledge, L-04: Hardware, L-05: Software, L-06: Data organization, L-07: File organization, L-08: Databases, L-09: Computer Networks, L-10: Java, L-11: Communication technologies, L-12: Electronic commerce, L-13: Data Security, L-14: HTML, L-15: XML


Exercises, Other forms of lectures, Research work: E-01: Introduction to ICT, E-02: Configuration and administration of the Windows operating system, E-03: Advanced use of word processors – Word, E-04: Advanced use of word processors – Word (continuation), E-05: Advanced techniques for working with tables – Excel, E-06: Advanced techniques for working with tables – Excel (continuation), E-07: Test: Windows+Word+Excel, E-08: Making presentations – PowerPoint, E-09: Internet and e-mail service, E-10: Making Internet presentations, E-11: Making Internet presentations (continuation 1), E-12: Making Internet presentations (continuation 2), E-13: Test: PowerPoint + Internet, E-14: Integrated test, E-15: Integrated test

Literature/Readings

1. Dejan Simić, Fundamentals of information and communication technologies, textbook, FON, Beograd 2011. 2. Dejan Simić, Workbook for fundamentals of information and communication technologies, FON, Beograd

2011. 3. Douglas E. Comer, Internetworking with TCP/IP Volume 1: Principles, Protocols, and Architecture,

Pearson Education, 2013. 4. V. Rajaraman, Introduction to Information Technology, Second Edition, PHI Learning Private Limited,

Delhi, 2013. 5. August E. Grant, Jennifer H. Meadows, Communication Technology Update and Fundamentals, Thirteenth

Edition, CRC Press, 2012.

6. The material in electronic form, FON, Beograd, 2013. The number of class hours per week Other classes:


Teaching methods

Lectures, Exercises, Practical Work, Consultation.



Participation in labs 40 Written exam 60


Level of studies: Undergraduate studies

Course:

Fundamentals of Quality

Teacher:Filipović V. Jovan,Vasiljević V. Dragan

Status of course: mandatory

Number of ECTS: 6

Condition for taking: /

Objective of the course:

To enable students to understand basic concepts and terminology of quality management, and establish basis for dealing with forthcoming courses.

Outcome of the course

A student is capable to understand basic quality management concepts, advantages and shortcomings regarding application of these concepts.

Content of the course

Theoretical classes: History of quality management. Development of quality science. Philosophies and trends in quality management. Criteria for defining quality and definitions of quality. Quality in production and service provision. Dimensions of product and service quality. Variations. Quality trilogy. Systems and systems thinking. Systems approach to quality. Process and process management. Quality management. Quality management system. Quality assurance. Integrated management systems. Effectiveness and efficiency. Process improvement (incremental, break-through, Benchmarking, Reengineering). TQM principles. Infrastructure, practices and tools of TQM

Practical classes: Presentation of goals, objectives and methods. Introduction to case studies. Workshop1: Quality and personal values. Workshop 2: History of quality. Workshop 3: Trends in quality management. Workshop 4: Customers and interested parties. Workshop 5: Quality trilogy. Workshop 6: Identification of basic concepts and definitions of process/service quality. Development of basic QMS documentation. Quality of product (hardware, software, processed materials and services). Development of quality characteristics for specific product

Literature: 1. Filipović, J., Đurić, M. Osnove kvaliteta, 2009, FON, Beograd 2. Filipović, J., Jovanović, B., Menadţment kvaliteta i standardizacija u informacionim sistemima i tehnologijama, FON, Beograd (in print) Number of classes Other classes

1 Theoretical: 2 Practical:2 Other forms: Study and research work:

Methods of conducting classes

Theoretical classes, practical classes, case study analysis, analysis and application of standards

Knolwedge assessment (maximum 100 points)

Pre-exam obligations Points Pre-exam obligations Points

Activity on classes 5 Written exam 25

Homework 10 Oral exam 20

Mid-term exam 25

Essay 15



Course:

Introduction to Game Theory

Teacher:Kuzmanović S. Marija,Martić M. Milan


ECTS points: 4

Prerequisites:

Course objective

The course is designed to introduce students to the basic concepts, principles, models and techniques of game theory and the possibility of their application in modeling and analyzing strategic interaction in the complex and interactive business environment.

Learning outcomes

Students will be trained in strategic and analytical thinking and application of concepts of game theory in modeling and solving real-world problems.


Theoretical instruction: P01: Introduction and basic principles: Course objectives. Terminology. Strategic Thinking. Understanding the rules. Rationality and Common Knowledge. Equilibrium. P02- P06. Concepts and Techniques: Simultaneous Games. Domination. Mixed games and uncertainty. Nash equilibrium. Sequential Games. Sequential Rationality and backward induction. Mixed Games. Repeated games. P07-P10. General classes of games and strategies: Cooperative and Non-cooperative games. Typical games. Prisoner's Dilemma – solving and application. Strategic use of information. Strategic Moves, Commitment and Credibility. P11-P15. Applications in economics, marketing, finance, computer science, political science. Military applications. Other applications.

Practical instruction: Modeling strategic interaction. Business games. Typical games: Prisoner's dilemma, Coordination, Battle of the sexes, Chicken game, Hawk and Dove. Analogy of the typical games with real situations through examples. Methods and techniques for solving the strategic equilibrium. The interpretation of the strategic equilibrium. Software for solving games and simulation. Case Studies: Price war, Market entry, Strategic investment, Negotiation, Auctions.

Literature/Readings

1. Krĉevinac, S. et al., Operaciona istraţivanja 1, FON, Beograd, 2006.

2. Stojanović, B., Teorija igara - elementi i primena, Sluţbeni glasnik, 2005.

3. Dixit A., and Skeath S., Games of Strategy, 2nd edition, Norton, New York, 2004.

4. Dixit A., and Nalebuff B., Thinking Strategically, Norton, New York, 1991

5. Presentations and exercises; 6. www.gametheory.net


Lectures:

2

Labs:

2


Teaching methods

Lectures accompanied by appropriate presentations and multimedia content. Exercises based on realistic and illustrative examples. Creative workshops based on interactive work with students through analysis of case studies, experimental games and simulations.



Class Participation 10 Written exam 30

Practical lectures 30

Seminar work 30



Course:

Basis of Computer Geometry

Teacher:Stojanović A. Milica,Vučković Đ. Milica


ECTS points: 4


Course objective: Actual methods of showing geometry objects. Solving geometry problems by computer.

Learning outcomes: After course, students will be able to create algorithms and problems for solving geometry problems.


Theoretical instruction: 1. Analytical geometry in the plane: line, curves of second degree.

1. Graphs: basic facts, usage of graphs in programming.

2. Finding the biggest convex subset in the plane.

3. Problem of finding the shortest paths in the graph.

4. Voronoi diagram in the plane.

5. Dissection of the set of points in the plane.

6. Constructing the convex hull in the plane.

7. Finding the nearest neighbors in the plane.

8. The shape of points sets.

9. Polygon: the basic facts

10. Known examples of triangulation in the plane.

11. Triangulation based on the usage of Voronoi diagram.

12. Generalization of problems into tree dimensional space.

13. Polyhedron and the problem of the triangulation in the space.

14. Seminar work.


Creating algorithms in field worked on the theoretical classes.

Literature/Readings

1. Edelsbrunner, H., Algorithms in Combinatorial Geometry, Springer – Verlag, Heidelberg, 1987. 2. Dragan Acketa, Sneţana Matić – Kekić, Geometry for informaticars, University in Novi Sad, PMF,

Novi Sad 2000. (in Serbian) The number of class hours per week Other classes:


Teaching methods: mentor and/or classical




Participation in labs Oral Exam 25

Projects 35


Degree level: Bachelor Academic Studies

Course:

Organization Basics

Teacher:Jaško O. Ondrej,Čudanov J. Mladen,Jevtić V. Miloš


ECTS points: 6

Prerequisites:

Course objective

The objective of the course is to introduce first year students with the basic concepts in organizational sciences, as well as to gain knowledge about the organization of business systems, that will provide basis for understanding particular aspects of the business system on senior years of study.

Learning outcomes

To get basic knowledge in the field of organization of business systems and to get skills and abilities to solve practical organizational problems.



Development of Organizational Sciences. Defining the concept, social width and importance of the organization. Organizational principles, methods, techniques, tools and instruments. Theories of organization. The strategic elements of the organization. Organization of business systems. The organization of work processes in manufacturing and other industries. Production management. Production facilities, calculating, synchronization. Productivity, definitions, factors, the importance of labour productivity. Organizing, structuring the organization, setting direction and planning the work process. Models of the organization. Models of organizational structures. The main institutional forms of organization.


The development of organization theory - Scientific Management. The development of organization theory - Administrative theory. The development of organization theory - Bureaucratic organizations. The development of organization theory - Theories of behaviour in organizations. Management Science. Contemporary organization theories. Work organization - analysis of technological alternatives, the organization of the production process. Methods for determining time standards of performance. Management and regulation - control of costs and inventories. Quality management. Labour productivity - mechanization, automation, innovation. Types of authority in the organization. Models of organizational structures - examples. The basic functions of companies - job descriptions.

Literature/Readings

1. Jaško, O., Ĉudanov, M., Jevtić, M. & Krivokapić, J. (2013). Osnovi organizacije i

menadžmenta. Beograd, Srbija: Fakultet organizacionih nauka. 2. Krivokapić, J., Todorović, I. & Komazec, S. (2013). Osnovi organizacije i menadžmenta –

praktikum. Beograd, Srbija: Fakultet organizacionih nauka. 3. Daft, R. L. (2009). Organization Theory and Design. Stamford, Connecticut, USA: Cengage

Learning. 4. Morgan, G. (2006). Images of Organization. London, UK: Sage Publications.


Lectures:2 Labs:2 Workshops: Research study:

Teaching methods

Monological method, demonstrative method, case study, learning through mutual work on practical problem solution, independent research and problem solving on the background of given problems.




Test 30 Oral exam 45


Degree level: Bachelor Academic Studies

Course:

Pedagogy with didactics

Teacher: Gordana Đ. Milosavljević


ECTS points: 4

Prerequisites:

Course objective

Introduction to the processes of education and upbringing from a social point of view. The course enables understanding of the basic principles of planning and organization of a teaching class. The aim is to train students for independent use of modern teaching methods and tools.

Learning outcomes

Students will be able to apply basic principles of pedagogy and didactis to plan, organize and implement teaching class.



Upbringing and education and as a basic pedagogical processes. The factors of personality development. The process of cognition and the learning process. Developing skills and habits. Motivating students, forms of cooperation and support. Encouraging teamwork. Electronic communication. The development of creativity. Methods of teaching. Forms of teaching. The resources in the classroom. The specifics of computer assisted instructions. Planning teaching work. The organization of teaching. The organization and management of teaching class. Types and structure of the class. Exposure, determination and exercise. Homework assignments. Testing and assessing. The relationship between students and teachers. Modern pedagogical documentation.


The exercises follows the learning units foreseen by lectures.

Literature/Readings

1. ĐorĊević,J., Trnavac, M., Pedagogija, Belgrade, Nauĉna knjiga, 2005. The number of class hours per week Other classes:

Lectures: Labs: Workshops: Research study:

2 2

Teaching methods

- Preparation and immediate realization of methodical units

- Lectures, discussions, case studies, simulation methods.





Degree level: Basic Academic Studies

Course:

Legal Basis of Information Systems

Teacher:Drakulić S. Mirjana


ECTS points: 5

Prerequisites:

Course objective: To enable students to understand legal aspects of implementation of information systems and phenomena related to computer networks (privacy and data protection, individual rights in cyberspace, intellectual property rights for software and databases, cyber security: authentication, authorization, identification).

Learning outcomes

Students can use enhanced knowledge, abilities and skills in solving legal problems in cyberspace; understanding legal framework of application of information and communication technologies and networks.



Concept, development and significance of Computer and Cyber law. Information society. Application of information and communication technologies and human rights. Personal data. Privacy and data protection. Protection of privacy. Data protection for organizations. Protection of software and computer software with intellectual property rights: patent, trademark, copyright, law for protection of competition, trade secret. The protection of databases with law on related rights, sui generis law, copyright law and law for protection of competition. The abuse of intellectual property on the Internet. Computer related crime: definition, types, characteristics. Cyber crime. Victims of Computer and Cyber crime. Digital evidence. Discovery. Cyber forensics. Court proceedings. Legal aspects of e-business

Practical instruction: Exercise, Other Teaching modes, Study research work

Concept of Computer and Cyber law. Personal data and protection. Commissioner for Information of Public Importance and Personal Data Protection: rights, responsibilities and competencies. Establishment of business organizations for the provision of information and communication services. Information and communication technologies and intellectual property. Patent registration. Legal protection of intellectual property rights. Copyright contract. Computer crime. Cyber crime. Cyber forensics. Collecting digital evidence. Forensic tools. Preparation of digital evidence for the court. E-business


1. Drakulić M., Basis of Computer Law, Society of Operational Researchers of Yugoslavia – DOPIS, Belgrade, 1996.

2. Bainbridge D., Computer Law, Harlow, Pearson Longman, 2000. 3. Mladenović D., Drakulić M., Jovanović D., International Law and Cyber Warfare, Vojno delo, year

LXIII, spring/2012. p. 9–39. 4. Hester M., Ford P., Computers and Ethics in Cyber Age, Belgrade, Official Gazette, 2009. 5. Drakulić M, Drakulić R, Internet regulation, study, RATEL, Belgrade, 2010. p. 188. 6. Reed C., Computer Law, Oxford University Press, Oxford, 2011. The number of class hours per week Other classes:

Lectures: 2 Exercise: 2 Workshops: Research study:

Teaching methods:

Conversation method, demonstration method, debates, case studies, learning by working together to solve practical problems, student’s independent research and problem solving through assigned tasks, consultation in preparation of project task, and independent work of students through learning and development of project task. Exercises are performed through e-learning application MOODLE



Activity in class 2 Progress tests/Final written test 30

Workshops 14 Oral exam 20

Case study/Debate 15

Tasks 14

Glossary 3

Student’s grade 2



Course:

Applied Operations Research

Teacher:Stanojević J. Milan,Makajić-Nikolić D. Dragana,Kuzmanović S. Marija,Savić I. Gordana


ECTS points: 5

Prerequisites: Operations research

Course objective

Course objective is to make students capable to recognize, model and solve real life optimization problems and to estimate company’s benefits from application of operations research. We aim to teach students about the possibilities and the application of software for solving optimization problems.

Learning outcomes

After passing the exam, a student will be capable to recognize an optimization problem, to model it and to use corresponding software packages for its solving.


Theoretical instruction: Overview of characteristic real world optimization problems in: production, supply chains, finance, marketing, services, etc. Possible approaches to modelling of optimization problems. Role, importance and application of software for optimization. Some algebraic modelling languages: AMPL, GMPL, OPL, LINGO, GAMS. Application of optimization software in the spreadsheet environment. Connection of optimization software to data bases. Overview of existing commercial solutions.

Practical instruction: Modelling of some optimization problems using selected algebraic language. Solving case studies using optimization software.

Literature/Readings

1. J. A. Lawrence, B. A. Pasternack, Applied Management Science: Modeling, Spreadsheet Analysis, and Communication for Decision Making, John Wiley & Sons, 2002.

2. R. Fourer, D. M. Gay, B. W. Kernighan, AMPL: A Modeling Language for Mathematical Programming, Duxbury Press, 2002.

3. A. Makhorin, Modeling Language GNU MathProg Language Reference, Free Software Foundation, 2013.

4. What’s Best, The spreadsheet solver, LINDO Systems Inc, 2011. 5. Users guides and tutorials for corresponding software packages.


Computer room 1

Lectures:

2

Labs:

2


Individual work

Teaching methods

Theoretical instructions are performed as block classes or by mentor work (depending on the number of students). For practical instructions case studies and work in computer room are used.



Participation in class 5 Written exam


Seminar paper 50



Course:

Programming I



ECTS points: 4

Prerequisites: Non

Course objective: Introduction to the core concepts of programming, software development and software engineering. Understanding the principles, rules and methods of programming and software development, as well as the basic algorithmic structures and data structures. Coding and testing: usage of an arbitrary imperative programming language. The use of software tools and basic software metrics.

Learning outcomes: Competence of students to develop software using the method of functional decomposition and structured programming in an imperative language.


Lectures: M01: Programming : concept, a general model, language, process. M02: The basics of the computer programming and the use of lower programming languages. M03: The higher programming languages and software paradigms; the basic elements of programming language (alphabet, identifiers, types, literals, expressions, operators, commands). M04 : The subroutines; structures, unions and arrays; declaration. M05: Pointers and dynamic memory management. M06: Constructing of structural algorithms. M07: Constructing of data structure. M08: Programming idioms. M09: Programming idioms /cont . / M10: Linear data structures. M11: Linear data structures /cont . / M12: Software development using algorithmic abstractions and data abstractions. M013: Fundamentals of software engineering.

Labs: L01: Programmer’s (software) tools. L02: Lower programming languages: examples. L03: Identifiers, types, literals, expressions, operators, commands. L04: Arrays; preprocessor directive. L05: U/I: streams and files. L06: Programming techniques. L07: Programming techniques /cont. / L08: Programming idioms. L09: Program idioms /cont. / L10: Linear data structures. L11: Linear structure podatataka /cont. / L12 Synthesis: Case Study. L13: Fundamentals of software engineering.


9. D.E. Knuth: The Art of Computer Programming, Vol. I, II; Addison-Wesley, 1969-1973 10. O.J. Dahl, E.W. Dijkstra, C.A.R. Hoare: Structured Programming, Academic Press, 1972 11. N. Wirth: Algorithms + Data Structures = Programs, Prentice-Hall, Englewood Cliffs, 1976 12. B.W. Kernighan, D.M. Ritchie: Programming language C, 2nd ed., Prentice-Hall, Englewood Cliffs,

1988 13. C.L. Tondo, S.E. Gimpel: The C Answer Book, 2nd ed., Prentice-Hall, 1993 14. A. Hansen: C Programming: A Complete Guide, Addison-Wesley, 1989 The number of class hours per week Other classes:

Lectures: 2 Labs: 2 Workshops: / Research study: / /

Teaching methods: Lectures: Lectures ex cathedra, and with the use of multimedia resources; explanation of the case study. Labs: computing, programming.




Tests (optional) 20 Oral exam 10

Project (required) 30


Degree level: BSc

Course:

Programming 2

Teacher:Devedţić B. Vladan,Jovanović M. Jelena,Tomić B. Bojan,Ševarac V. Zoran

Course status: required

ECTS points: 6

Prerequisites: Programming 1

Course objective

Mastering programming techniques using the Java programming language. Learning outcomes

Students' proficiency in programming at an intermediate level in the currently most popular programming language and using an appropriate software development environment.



Review of basic programming concepts using the Java programming language. Classes and Objects. Methods and static methods. Constructors. Advanced programming with objects. Arrays as objects. Advanced programming with strings. Interfaces. Important packages, classes and interfaces of the Java API. Exception handling. Working with files. Collections of objects. Iterators. Java classes for working with the most important data structures. JDBC. Reflection. Processing events. Graphical user interface 1. Graphical user interface 2. Preparation for the exam 1. Preparation for the exam 2.


Introduction to the use of software tools for developing Java programs . Creating programs that illustrate advanced work with objects. Repetition exercises 1. Writing programs that illustrate writing a custom class. Creating programs that illustrate working with Java interfaces. Repetition exercises 2. Creating programs that illustrate Java exceptions. Creating programs that illustrate working with files. Development of programs that illustrate Java collections. Creating programs that illustrate working with the most important data structures. Development of programs that illustrate Java reflection. Repetition exercises 3. Creating a program with a graphical user interface. Repetition exercises 4. Preparation for the exam 1. Preparation for the exam 2.

Literature/Readings

1. Programming can not be learnt by reading books. Only individual practical work on a computer with regular guidance by the teacher and non-formal consultations with tutors (or any other experienced programmer) can lead to proficiency in programming. Those who still insist on some kind of textbook may use any book that describes in detail the programming language

Java. 2. Additional reading: CD with software and worked-out examples and links to numerous worked-

out examples on the Web. The number of class hours per week Other classes:

Lectures: 2 Labs:1 Workshops: 1 Research study:

Teaching methods

Lectures: the teacher programs on a computer, the students follow and discuss details of the program with the teacher. Labs: the students themselves create simple programs in Java, guided and assisted by the tutor.



Development of a simple program on a computer.

100



Course:

Programming data access



ECTS points: 4

Prerequisites: Non

Course objective: Understanding of the principles, rules and methods to access data in the software system. Introduction to the key concepts of data access, as well as the problems and their solutions.

Learning outcomes: Competence of students to develop software to access the data using the appropriate methods and technologies.


Lectures:

1. Introduction: objectives, lecturing units, mode, method of examinations, literature (readings), teachers and staff. Basic concepts. The architecture of software systems: presentation layer, application layer, data layer. Mastering the various implementing models and technologies / implementation of data access using different platforms

2. Working with Files, the Registry, and Active Directory. 3. Access to the data using the Java platform: The process of connecting Java programs and the DBMS;

The method of execution of operations on the database; Examples of execution of DDL / DML / DQL query from Java applications.

4. Access to the data using the NET platform: Using NET Data Providers (connection to the database, query, restore data using DataAdapter-a); Using DataSet (DataSet objects DataRelation objects, sorting and searching, strictly typed DataSet, forwarding queries to the database);

5. XML programming (XML standards, XPath, XQuery, XSLT, XML and ADO.NET, XML serialization).

6. Access to data by using XML Web services: design and implementation; The construction of service- oriented software architecture.

7. Basics of programming database objects. 8. Construction of Data Access Layer-a. 9. Language Integrated Query (LINQ): Architecture, Lambda expressions, Late evaluation; LINQ and

DataSets, LINQ, and SQL; LINQ and update data, LINQ and XML, LINQ and IEnumerable interface; Standard LINQ operators.

Labs: The order of labs exercises and labs exercise content is fully compliant with lecturing units.


15. C. Nock: Data Access Patterns: Database Interactions in OO Apps, Addison-Wesley, 2005. 16. D. Sceppa: MS ADO.NET Core Reference, Microsoft Press, 2012. 17. S. McConnell: Code Complete: A Practical Handbook of Software Construction, MS Press, 2004. 18. S. Stiefel, L. Oberg: App Development using C# and .NET, Prentice Hall PTR, 2003. 19. S. Robinson, et al. : Professional C# Programming, Wrox Press, 2002. 20. J. Zukowski, Java 6 Platform Revealed: Apress, Berkeley, 2006. 21. J. Hummel: LINQ: The Future of Data Access, 2006.


/ Lectures: 2 Labs: 2 Workshops: / Research study: /

Teaching methods: Lectures: Lectures ex cathedra, and with the use of multimedia resources; explanation of the case study. Labs: case studies, programming.




Project (required) 30 Oral exam 20



Course:

Programming languages

Teacher:Vučković Đ. Milica,Nešković N. Siniša


ECTS points: 5

Prerequisites:

Course objective The aim of this course is to provide students with the necessary theoretical and practical knowledge of the fundamental concepts of modern programming languages. Additionally, this course also introduces students to programming language translators.

Learning outcomes The acquired knowledge of the concepts and characteristics of modern programming languages will enable students to select and use the appropriate languages when designing and developing information systems.



Introduction to programming languages. Syntax, semantics and implementation of programming languages. Lexical and syntax analysis. Programming language implementation: implementation methods. Overview of scanner and parser generator tools. Overview and analysis of programming language paradigms. Abstractions in programming languages. Base abstractions. Structural abstractions. Procedural abstractions. Data abstractions. Fundamental concepts of object-oriented programming languages. Fundamental concepts of functional and logic programming languages. Introduction to «markup» languages: XML and XML technologies. XML document processing: XML parser models and their implementation in a specific implementation environment.


Practical instructions closely follow the lectures. In the course of these practical instructions students gain hands- on knowledge of the concepts and characteristics of different programming language paradigms through the design and coding of programs in a chosen set of languages.

Literature/Readings

1. M. Vuĉković, Fundamentalni koncepti programskih jezika, lectures, at www.pjp.fon.rs. 2. M. Vuĉković, M. Petrović, N. Turajlić, Praktikum iz programskih jezika, course notes, at

www.pjp.fon.rs. 3. R.W. Sebesta, Concepts of Programming Languages, Ninth edition, Addison-Wesley Publishing

Company, 2010. The number of class hours per week Other classes:


Teaching methods

Lectures. In the course of practical instructions students gain hands-on knowledge of the concepts and

characteristics of different programming language paradigms through the design and coding of programs in a chosen set of languages. Project assignments for individuals or small groups.




Oral exam 30



Course:

Programming language translators

Teacher:Vučković Đ. Milica


ECTS points: 5

Prerequisites: -

Course objective The aim of this course is to provide students with the necessary theoretical and practical knowledge of programming language translators and the tools which have been developed for their implementation.

Learning outcomes The acquired knowledge of the concepts and characteristics of modern programming language translators will provide students with a better understanding of the way programming languages are implemented, which directly influences their ability to select and use the appropriate languages when designing and developing modern software applications. In addition, the acquired knowledge of parser generator tools can also be applied when designing and implementing domain-specific languages.



Introduction to programming language translators. Lexical analysis: regular expressions and finite automata. Syntax analysis. Parser types (top-down and bottom-up parsing). Semantic analysis. Run-time environment. Intermediate code generation. Code generation. Code optimization. Interpreters and hybrid implementation systems. Overview of scanner and parser generator tools. Using parser generator tools to develop a chosen domain-specific language.


Practical instructions closely follow the lectures. In the course of these practical instructions students gain hands- on knowledge of the concepts and characteristics of programming language translators and the tools which have been developed for their implementation.

Literature/Readings

1. A.V. Aho, M.S. Lam, R. Sethi, and J.D. Ullman, Compilers: Principles, Techniques, and Tools, Second edition, Addison-Wesley, 2006.

2. T. Mogensen, Introduction to Compiler Design, Springer, 2011. The number of class hours per week Other

classes: Lectures:

2

Labs:

2

Workshops:

1

Research study:

Teaching methods

Lectures. Through practical instructions students gain hands-on knowledge of the concepts and characteristics of

programming language translators and the tools which have been developed for their implementation.



Project assignment 70 Oral exam 30


Degree level: Bachelors degree

Course:

Production systems

Teacher:Radović M. Milić,Slović D. Dragoslav


ECTS points: 6

Prerequisites: /

Course objective

The objective of this course is to introduce students to basic processes and operations in production and service systems, and their relations. Students will learn basic concepts of process planning, eqipment selection, layout, waste elimination, by using specific engineering and management methods.

Learning outcomes

Conceptual knowledge to classify and categorize principles, theories, and models to understand basic processes and operations in production and service systems, and their relations.



Basic terms of production organization; Basic principles of modern production philosophy; Operations in manufacturing and service business systems; Process approach; Process engineering and reengineering; Business process organization and management; Product portfolio optimization; Technological process as a basis for business organization; Optimization of number and size of batches; Manufacturing equipment selection; Calculating optimal number of machines, operators, and work places; Work scheduling; Production system’s operation analysis; Creative work-shops; Final instructions for written exam.


Calculating the level of organization of business systems; Project assignment – determining organization level of business systems; Product portfolio optimization; Optimization of number and size of batches; Manufacturing equipment selection; Calculating optimal number of machines, operators, and work places; Functional layout, cell layout, and product layout; Work scheduling; Production system’s operation analysis; Revision exercises.

Literature/Readings

Radović M., Proizvodni sistemi, FON, Beograd, 2007.

Radović M., Proizvodni sistemi, proizvodnja, analiza i upravljanje, primeri i zadaci, FON, Beograd,

2007.

Chryssolouris G., Manufacturing Systems: Theory and Practice, Springer, New York, 2006.



Teaching methods

Power Point presentations, business case presentations, active participation in problem solving, workshops, individual work on project assignments







Course:

Information Systems Design

Teacher:Marjanović M. Zoran,Aničić M. Nenad,Babarogić S. SlaĎan



Prerequisites: /

Course objective

Students will gain knowledge about conventional and object-oriented models and approaches for analysis and logical design of IS.

Learning outcomes

Students will be capable to analyze and specify user requirements, to model database and applications using patterns and CASE tools.



Introduction. Development plan. Analyzing requirements – functional analysis. Logical design of structure and system dynamics using ER diagram. Conventional models for analyzing and logical design. SSA. ER diagram. Conventional models overview. Object-oriented approach in logical design of IS. Analyzing requirements – use cases. System sequence diagram. Conceptual system model. Class diagram. Patterns in IS modeling. Description of system dynamics. Logical design of database. MDA. MDD. OCL. QVT. Transforming conventional models to relational model. CASE tools. Meta-modelling. Overview of methodologies and standards in IS development. Exam preparation.


Analysis and logical design of IS. Functional decomposition. SSA – basic examples. SSA – more complex examples, data dictionary. ER diagram. IDEF1X, IE. Use cases. Class diagram. Patterns for system analysis phase. Multi-tier application architecture. Sequence diagram – basic examples. Sequence diagram – more complex examples. Statechart diagram. Final class diagram. Conceptual models transformation. Exam preparation.

Literature/Readings

1. George, Joey F., Batra, Dinesh, Valacich, Joseph S., Hoffer, Jeffrey A., Object-oriented systems analysis and design, Pearson Prentice Hall, 2004.

2. Hoffer, Jeffrey A., George, Joey F., Valacich, Joseph S., Modern systems analysis and design,

Pearson Prentice Hall, 2005 3. Larman C., Applying UML and Patterns-An Introduction to Object-Oriented Analysis and

Design, 3th ed., Prentice Hall, 2004. 4. Materials and scripts from lectures and labs, Laboratory for Information systems, FOS 5. e-Presentations on course site pisbp.fon.bg.ac.rs



Teaching methods

Lectures (30 classes) and labs (30 classes). Case studies.







Course:

Software design

Teacher:Vlajić S. Siniša,Lazarević D. Saša


ECTS points: 6

Prerequisites: -

Course objective: Gaining knowledge about the basic principles, strategies and methods of software design. Review of the principles and techniques of designing the user interface, application logic and database. The adoption of a method of software design using design patterns and architecture patterns. Introduction and use of advanced concepts of modern object-oriented programming languages (Java or C #).

Learning outcomes: Ability of students to: a) design software in accordance with modern methods of software development b) implement software systems using modern object-oriented programming languages (Java or C #).



Basics of software design. Context of design in the software development life cycle (Unified Software Development Process, Larman software development method, ...). Strategies and methods of software design. Architecture design. Designing the user interface. Design of application logic. Projecting the database. Designing algorithms. Architecture and design patterns . Notations and tools for the software design. Implementing technology. Work with students to develop logical structure of a seminar paper.


The working environment for writing programs. Concurrent programming . The work on the network - sockets. Call remote methods (RMI). Protection. Working with the database. Connecting a GUI to a database over the network. Reflections. JAXP and JAXB XML technology. Work with students to develop and implement seminar paper.

Literature/Readings

Basic literature:

1. Siniša Vlajić, Dušan Savić, Vojislav Stanojević, Ilija Antović, Miloš Milić: Software design – advanced software technologies, Zlatni presek, (on serbian language) ISBN: 978-86-86887-03-0, Belgrade, 2008. 2. Siniša Vlajić, Ćirić Vidojko and Dušan Savić: Software design (Practicum for Java programming language), ISBN: 86-904747-0-6, Belgrade, 2003. The most important parts of the book are available to

students at the following address: http://silab.fon.rs/index.php?option=com_docman&task=doc_download&gid=2&&Itemid=56

(on serbian language)

3. Siniša Vlajić: Software design, book in preparation, Belgrade, 2014. (on serbian language)

Additional literature:

1. Ivar Jacobson, Grady Booch, James Rumbaugh: The Unified Software Development Process,

Rational Software Corporation, Addison-Wesley, 1999. 2. Craig Larman: Applying UML and Patterns, Prentice Hall, New Jersy, 1998 3. Erich Gamma, Richard Helm, Ralph Johnson, JohnVlissides: Design patterns, Addison : Wesley, 18th

Printing, September 1999. 4. Cay S. Horstmann, Gary Cornell: core JAVA 2, Volume II – Advanced Features, Sun

Microsystems Press , 2000, California, USA.


1 Lectures: 2 Labs: 1 Workshops: Research study:

Teaching methods







Oral exam 40


Degree level: Bachelor

Course:

Psychology

Teacher:Mihailović M. Dobrivoje


ECTS points: 4

Prerequisites:

Course objective

The aim is to introduce students with psychological concepts relevant for organizational behavior, explaining psychological terminology, as well as the theoretical and methodological principles applicable in the organizational context. Focus of the course is on psychological aspects of managing human resources.

Learning outcomes

Students should be able to recognize personal and interpersonal challenges in the organizational context and to be competent in application of psychological principles in order to resolve related issues.



Psychology as a science and psychological side of work. Personality, personality traits, measurement. Work psychology: scope, objectives and methods – job analysis. Professional orientation: process of choosing profession. Procedure and modern tendencies in professional selection; forecasting work behavior. Job adaptation: adaptation problems and methods of job techno-psychophysiology. Job absenteeism and turnover. Psychological aspects of injuries at work. Introduction to organizational psychology. Social and work groups. Personality and organization: types and problems. Leadership: term, theories and psychological problems. Work motivation: term and theories, factors and managing motivation. Communication in organization: process, types, difficulties in communication. Stress in organization: term, phases, types, sources, consequences, management.


Subject and tasks of psychology – workshop. Instructions for writing essay. Job analysis – example. Comparative analysis of selection of profession – discussion. Techniques of professional selection – job interview role play. Defense mechanisms – workshop. Work injuries: example analysis. Preparation for test 1 – quiz. Presentation of essays – part 1. Social and work groups: case study. Presentation of essays – part 2. Leadership problems and theories of leadership: case study. Motivation: case study. Problems of

communication in organization: case study. Stress: individual stressful events – discussion.

Literature/Readings

Mihailović, D. Psychology of Work and Organization, FOS, Belgrade, 2010.


Lectures: 2 Labs: Workshops: 1 Research study:

Teaching methods

Lectures, interactive classes, solving concrete assignments (workshops), experiential learning through role playing, group discussions, case study, teamwork on essay writing.



Participation in class 10 Tests 55

Essay 5 Oral exam 30



Course:

Computer networks and telecommunication

Teacher:Starčević B. Dušan,Minović V. Miroslav,Milovanović M. Miloš


ECTS points: 6

Prerequisites:

Course objective

Enabling understanding operation of computer networks and telecommunication systems, as well as acquiring practically usable knowledge needed for design and implementation of distributed information systems.

Learning outcomes

Students will acquire basic knowledge and skills needed for developing computer networks as well as programming network applications for Internet and local computer networks.



P- 01: Computer networks and the Internet . P- 02: Application layer . Protocols at the application layer. Web and HTTP . P-03 : Application layer . File Transfer Protocol : FTP . E-mail on the Internet . DNS Services directory on the Internet . P-04 : Application layer . P2P . Socket programming using TCP. Programming with UDP sockets . Construction of a simple Web server . P- 05: The transport layer . Transport-layer services . Multiplexing and demultiplexing . Connectionless data transfer - UDP. P- 06: The transport layer . Reliable data . P- 07: The transport layer . Connection- oriented data transfer - TCP. Principles of congestion . Congestion management in TCP . P- 08: Network layer. Network service model. Virtual circuit . Datagram networks. P- 09: Network layer . Router . Internet protocol . Routing algorithms. P- 10: Network layer . Routing in the Internet. Broadcast and multicast routing . P - 11 : Data link layer . Data link layer services. Techniques for detecting and correcting errors . P- 12: Data link layer . Protocols for multiple access . Addressing the data link layer . P - 13 : Data link layer . Ethernet . Hub , bridge and switch. P-14 : Data link layer . PPP protocol . ATM networks. P-15 : Data link layer . MPLS .

Literature/Readings

1. Kurose, Ross, Umrežavanje računara CET, Beograd, 2009. 2. Dušan Starčević i saradnici, Računarske mreže i telekomunikacije – praktikum, FON, Beograd, 2013. 3. White Curt M. Data communications and computer networks: a business user's approach Thomson cop.

Bosto, 2007 The number of class hours per week Other classes:


Teaching methods

Lectures, labs




Project 30



Course:

Modern Software Architectures

Teacher:Đurić O. Dragan,Devedţić B. Vladan


ECTS points: 6

Prerequisites: Software Project Management

Course objective

Mastering contemporary software architecture and the techniques and practical skills for applying them.

Learning outcomes

Students’ ability to implement software projects, in technical sense and as an everyday work in a software development company.



Software architecture. Software architecture examples. Three-tier, n-tier and architectures adapted for Internet applications. Software architecture standardization. Contemporary frameworks. Middleware design. Integration frameworks. Persistence and data connectivity frameworks. Web user interface. Web user interface frameworks. Study example.


Labs. Other forms of teaching. Research study work. Work with tools and frameworks. Practical project.

Literature/Readings

• Digital learning resources available on the course CD. • Examples of practical software projects. • Open source software frameworks and tools, as well as their documentation and useful tutorials are

freely available on the Web.

• Labs consists of practical work on students’ own projects under the supervision of the assistants.


– Lectures:

2

Labs:

2

Workshops:

-

Research study:

–

Teaching methods









Course:

Simulation and simulation languages

Teacher:Radenković LJ. Boţidar,Marković M. Aleksandar,Despotović-Zrakić S. Marijana,Bogdanović M. Zorica,Barać M. Dušan,Labus B. Aleksandra


ECTS points: 6

Prerequisites:

Course objective

The aim of the course is to give clear and comprehensive overview the basic ideas and possibilities of computer simulation.

Learning outcomes

Students gain knowledge and skills related to computer simulation applications and simulation models development. Students mastered basic techniques, methods and computer simulation conepts.


Theoretical instruction: Modeling and models. Classification of models. Model parameters. Validation and verification. Simulation tools. Simulation of continuous systems. Languages for simulating continuous systems. Discrete event simulation. Languages for discrete-event simulation. Web simulation. Distributed and parallel simulation. Artificial intelligence and simulation. Probability and statistics in the simulation. Virtual reality. 3D modeling.


Simulation of continuous systems, CSMP. Discrete event simulation, GPSS. Development of 3D model using Blender software solutions. Integration and implementation of 3D models in a web environment using X3D technology.

Literature/Readings

1. E-resources, available at www.elab.rs 2. Raĉunarska simulacija, B. Radenković, M. Stanojević, A. Marković, Fakultet organizacionih nauka,

Saobraćajni fakultet, 2009. 3. J. Banks, J.S. Carson II, B. L. Nelson, D. M. Nicol, Discrete-Event System Simulation (Fifth

Edition), Pearson Education, Inc. 2010. ISBN: 978-0136062127 4. M.F.Shiratuddin, K.Kitchens, D.Fletcher, Virtual Architecture: Modeling and Creation of Real-Time

3D Interactive Worlds, 2008, Lulu Press, USA. 5. L. Ahearn, 3D Game Environments, Elsevier, Inc. 2008. ISBN: 978-0-240-80895-6. 6. G.Burdea, P.Coiffet, Virtual Reality Technology. Hoboken, New Jersey: John Wiley and Sons. 7. X3D International Standard. (2013). Information technology — Computer graphics and image

processing — Extensible 3D (X3D) ISO/IEC 19775-1:201. The number of class hours per week Other classes:


Teaching methods




Assignements 50 Written exam 25

Oral exam 25


Degree level: Under graduate academic studies

Course:

Decision support systems

Teacher:Suknović M. Milija,Delibašić V. Boris


ECTS points: 4

Prerequisites: /

Course objective

Students are solving world decision making problem through development of decision support system.

Learning outcomes

Students are capable for decision making models development. Students should gain skills for work in business intelligence tools.


Theoretical instruction

01: Introduction to Decision support systems and Business intelligence. 02: Applications of Decision support systems and Business intelligence systems. 03: Descriptive analysis and visualization – case studies. 04: Introduction to data warehousing and reporting. 05: Data warehouses - case studies. 06: Data warehouse development. 07. Reporting systems development. 08. Introduction to data mining. 09: Data mining system design. 10: Basic data mining algorithms and their applications. 11: Advanced data mining algorithms and their applications. 12: Evaluation and application of data mining models. 13: Projects presentation.

Practical instruction

01: Project tasks definition and forming of project teams. 02: Introduction to software environment for basic data analysis. 03: Descriptive data analysis and visualization. 04: Definition of data structure, possible reports and analyses. 05. Data warehouse design. 06: Cleansing, integration and loading the data into Data warehouse. 07. Reporting system design. 08: Introduction with software environments for data mining. 09: Project tasks definition for data mining project. 10: Introduction with requirements of the algorithms and data adoption for algorithm application. 11: Parameterization, algorithm execution and model interpretation. 12: Evaluation and model revision.

Literature/readings

1. Suknović M, Delibašić V (2010) Business intelligence and decision support systems, Faculty of Organizational sciences, Belgrade, Serbia.

2. Delibašić B, Suknović M (2009) Machine learning algorithms for data mining, Faculty of Organizational sciences, Belgrade, Serbia.


Lectures: 2 Labs: 2 Workshops: Research studies:

Teaching methods

At begining of the course, students are applying for project that should be solved in 12 weeks. Besides theoretical teaching, lab exercices are organized as well as weekly group consultations.


Pre-exam requirements Points Final Exam Points

Project proposal 80

Oral exam 20



Course:

Open source software

Teacher:Ševarac V. Zoran


ECTS points: 6

Prerequisites: none

Course objective

To learn about open source software development: well known open source projects, open source strategies, development models, development environments, tools, licensing, and team work.

Learn about the open source software development process, practices and successful open source projects. To acquire practicall skills in software development, and learn about various software development tools.

Learning outcomes

Learn about open source software development model, process and tools. Students will acquire practical softwae development skills. Learn how to use and extend existing open source software.


Lectures.

Introduction. Basic concepts and philosophy about open source software development. Open source software life cycle: planning, starting, maintainance, development and licensng. Tools. Tools and environments for open source software development (version control, Integraded development environments, and testing). Software design. Design of basic domain classes , public programmin interface –API, and documenting.

Labs

Open source project examples: NetBeans, Neuroph, JMonkeyEngine

Software development on NetBeans Platform: module system window system, dialog system, nodes system, pallete, plugin system, update system.

Software development using open source frameworks: Neuroph framework and JMonkeyEngine.

Literature/Readings

[Feller, J. 2001], Understanding Open Source Software Development, Addison-Wesley Professional, ISBN 978-0201734966

[Fogel, K., 2005], Producing Open Source Software: How to Run a Successful Free Software Project, O'Reilly Media, ISBN 978-0596007591, ONLINE: http://producingoss.com/

[Javier A. Ortiz, Miloš Šilhanek, 2012], NetBeans Platform Cookbook, ONLINE: http://wiki.netbeans.org/BookNBPlatformCookbook


– Lectures:

2

Labs:

2

Workshops:

-

Research study:

–

Teaching methods

Lectures: slides and examples related to open source software projects.

Labs.students work on open source projects in teams or on their own, supervised by teaching assistant.





Project (conceptual solution)



Course:

Software patterns

Teacher:Vlajić S. Siniša

Course status: Election

ECTS points: 4

Prerequisites: -

Course objective: Understanding patterns in a general sense in the context of the development of a software system. The possibility of practical use patterns in the phases of design and implementation of a software system. Getting to know the existing mathematical formalism to describe patterns.

Learning outcomes: Ability of students to use patterns in the phases of design and implementation of a software system.



The purpose of the patterns and their place in the software development process. The general form of patterns. Patterns of requirements gathering and analysis. Design patterns (micro and macro architectural patterns). Implementation patterns. Patterns testing. Formalization of the patterns.


Design patterns, micro-architectural patterns (GOF patterns), macro architectural patterns (MVC) implementation patterns.

Literature/Readings

Basic literature:

1. Siniša Vlajić: Software patterns, ISBN: 978-86-86887-30-6 (on serbian lanquage), Belgrade 2014

Additional literature:

1 E. Gamma et al.: Design Patterns: Elements of Reusable Object-Oriented Software, Addison-Wesley, 1995.

2. M. Fowler: Patterns of Enterprise Application Architecture, Addison-Wesley, 2003.

3. M. Fowler: Analysis Patterns: Reusable Object Models. Addison-Wesley. Addison-Wesley, 1996.

4. C. Larman: Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design, Prentice-Hall, 1998.

5. F. Buschmann et al.: Pattern-Oriented Software Architecture: A System of Patterns, John Wiley &

Sons, 1996.



Teaching methods







Oral exam 50



Course:

Software Engineering

Teacher:Đurić O. Dragan


ECTS points: 6

Prerequisites: none

Course objective

Mastering basic and advanced concepts of Software Engineering

Learning outcomes

Students’ ability to use principles and techniques of contemporary software engineering.



Basic concepts of software development process, modelling and the UML language, software design patterns and refactoring. Use cases, domain modelling and class diagrams. Software modelling tools. Advanced structural modelling tools. Advanced concepts of behaviour modelling. Design patterns – idea and survey. Basic analysis patterns. The notion and principles of refactoring. Basic refactorings and refactoring tools. Advanced concepts of design patterns. Advanced concepts of analysis patterns. The skills of combining and using the learnt concepts. Review.


Labs. Other forms of teaching. Research study work. Getting to know the development environment. Software modelling tools. Use case diagrams. Structural diagrams. Behavior diagrams. Design patterns. Analysis patterns. Refactoring. Review.

Literature/Readings

Martin Fowler – UML Distilled 3rd Edition, Addison-Wesley, 2004.

Martin Fowler – Analysis Patterns, Addison-Wesley, 1997.

Erich Gamma et. al. – Design Patterns: Elements of Reusable Object-Oriented Code, Addison-Wesley, 1995.

Martin Fowler – Refactoring: Improving the Design of Existing Object-Oriented Code, Addison-Wesley, 1999.


– Lectures:

2

Labs:

2

Workshops:

-

Research study:

–

Teaching methods









Course:

Sociology

Teacher:Miladinović M. Slobodan,Petrović M. Dalibor


ECTS points: 5

Prerequisites:

Course objective: The student should acquire basic knowledge of sociology, to learn about the major social categories and principles that have been brought in an organizational context and to introduce the main features and characteristics of our society and that this knowledge can be used in practice, ie. to understand the social context of organizational phenomena and to understand the sociological way of thinking the same.

Learning outcomes: Acquisition of basic sociological knowledge with practical ability to recognize social categories and their application


Theoretical instruction: P-01: Introductory class, Sociology as a science, the notion of the subject of sociology; Q-02: Groups and organizations; P-03: Scientific and technological development and society; P-04: Social values; P-05: Social power; P-06: The social structure: class and the elite; P-07: The class structure of our society; P-08: Social mobility; P-09: The contemporary social systems; P-10: The globalization of modern society; P-11: A society in transition; P-12: Ecology and Society; P-13: Labor; P-14: Organized labor; P-15: Economic Democracy and Participation

Practical instruction: V-01: Introductory class, Sociology as a science, the notion of the subject of sociology; V-02: Social Research; V-03: Groups and organizations; V-04: Scientific and technological development and society; V-05: Social values; V-06: Social power; V-07: The social structure; V-08: Exercises of repetition; V-09: Social mobility; V-10: The contemporary social systems; V-11: The globalization of modern society; V-12: Society in Transition; V-13: Ecology and Society; V-14: Labor and organized labor; V-15: Exercises of repetition.

Literature/Readings: dr Slobodan Miladinović: Uvod u sociologiju organizacije, FON, Beograd, 2007.


Lectures:

15*2=30

Labs: Workshops:

15*1=15

Research study:

Teaching methods

Frontal teaching, Group and individual work, Mentoring, Presentation of seminar papers, Colloquium



Participation in class 10 Written test 30



Degree level: BSc

Course:

Statistics



ECTS points: 6

Prerequisites:

Course objective: Introduction to basic methods of statistical analysis and its application in solving practical problems.

Learning outcomes Students will be able to model and solve practical statistical problems and give appropriate conclusions by using basic statistical methods.



T01: Statistical interference, population, sample. T02: Statistics and their distributions. T03: Theory of estimation, criteria for choice of estimates. T04: Maximum likelihood method. T05: Confidence intervals. T06: Confidence intervals (continuance). T07: Hypothesis testing, parametric tests. T08: Parametric tests (continuance). T09: Parametric tests (continuance). T10:Non-parametric tests. T11: Non-parametric tests (continuance). T12: Regression models. T13: Method of ordinary least squares. T14: Testing hypothesis about parameters of linear regression. T15: Method of analysis of variance.


P01: Population, sample. P02: Statistics and their distributions. P03: Statistics and their distributions (continuance). P04: Maximum likelihood method. P05: Confidence intervals. P06: Confidence intervals (continuance). P07: Practical exercise. P08: Hypothesis testing, parametric tests. P09: Parametric tests (continuance). P10:Non-parametric tests. P11: Non-parametric tests (continuance). P12: Regression models. P13: Regression models (continuance). P14: Method of analysis of variance. P15: Practical exercise.

Literature/Readings

1. Vuković N., Bulajić M., Osnove statistike, Fakultet organizacionih nauka, Newpress, ISBN: 978-86-7680-293-7, Beograd, 2014

2. Bulajić M., Vukmirović D., Radojiĉić Z., Jeremić V., Totić S., Đoković A., Dobrota M., Statistika zbirka zadataka, FON, 2013.

3. Vuković N., PC statistika i verovatnoća, FON, 2005. The number of class hours per week Other classes:







Colloquium 20

Seminar 20


Degree level: BSc

Course:

Statistical Inference

Teacher:Bulajić V. Milica


ECTS points: 4

Prerequisites:

Course objective

Introduction to the application of predictive statistical models. Offers detailed knowledge of possibilities and methods of statistical analysis, as well as more detailed insight in methods of statistical inference.

Learning outcomes

Students will be able to make the adequate predictions on heterogeneous data in order to achieve greater accuracy while making conclusions and thus gaining the better assurance in the decision-making process. Students will be capable apply the statistical software package in solving these problems.



L-01: Distributions. L-02: Distributions of linear forms. L-03: Parametric inference.L-04: Non- parametric inference. L-05: Gauss-Markov model. L-06: Bayes inference. L-07: The application of software in statistical inference L-08: The contingency tables analysis. L-09: Binaryzation of data. L-10: Discrete methods for analysis of multidimensional data. L-11: Cochran – Mantel – Haenszel testing. L- 12: Coefficient of preference. L-13: Relative risk and ratio. L-14: The applicability and model validation. L-15: Parameter valuation based on data.


P-01: The examples of applications of distributions. P-02: Simulations of distributions. P-03: The case study of parametric inference. P-04: The case study of non- parametric inference. P-05: Markov chains. P-06: Simulation of Bayes’s inference. P-07: The entropy. P-08: The concept of minimal entropy. P-09: 2X2 tables. P-10: 2x2xK tables. P-11: Odds ratio. P-12: Logistic regression. P-13: Logit regression models. P-14: The analysis of missing data. P-15: The analysis of multiple choice answers.

Literature/Readings

1. Casella G., Berger R., Statistical Inference, Wiley John&Sons, Incorporated,1999. 2. Barnett V., Comparative Statistical Inference, Wiley, John&Sons, Incorporated 1999. 3. Spiegelhalter D. J., Abrams K. R., Myles J. P., Barnett V., Bayesian Approaches to Clinical

Trials and HealthCare Evaluation, Wiley, John&Sons, Incorporated, 2004. 4. Maddala G.S., Introduction to Econometric, John Wiley & Sons, 2001. 5. Lovrić, M., Metodi neparametarskog statističkog zaključivanja, Ekonomski fakultet, 2002.



Teaching methods

The traditional way of lecturing, with the use of whiteboard and computer





Colloqia 20

Seminar work 20



Course:

Data Structures and Algorithms

Teacher:Nešković N. Siniša,Vučković Đ. Milica


ECTS points: 6

Prerequisites: -

Course objective

To introduce students with the concept of data structures, their efficient computer realization as well as various algorithms for their manipulation

Learning outcomes

Students will be enabled in solving practical problems to analyze, select and successfully apply data structures and algorithms which are the most suitable for solving the given problem in information system development



Data abstractions. The notion of data structures. Types of data structures. Linear data structures. Stack, Queue, List. Definition based on Abstract Data Types. Implementation using array and dynamic structures (linked lists). Analyses of algorithms efficiency. Searching linear data structures. Binary search. Interpolation search. Sorting – the concept. Basic and advanced sorting algorithms. Trees – basic concepts. Binary trees. Binary search trees and AVL trees. Searching multiway trees. B, B* and B+ tree. Search based on hashing. Graphs and networks. Algorithms on graphs.


Procedural abstraction in Java. Data abstractions in Java. Implementation of linear data structures. Searching linear structures. Solving problems with linear structures. Study of sorting algorithms. Implementation of trees in Java. Solving problems with tree structures. Tree transformations. Exercises with AVL trees. Exercises with B-trees. Implementation of hashing search. Exercises with graphs and networks.

Literature/Readings

• S. Nešković, Strukture podataka, skripta. • S. Nešković, D. Stojimirović, Zbirka zadataka iz struktura podataka i algoritama, skripta • Slajdovi sa predavanja u e-formi i izvorni kod za primere sa stranice http://strukture.labis.fon.rs/ • Robert Sedgewick: Algorithms in Java, Third Edition, Addison Wesley, 2004, ISBN: 0-201-36121-3

Thomas H. Cormen et al: Introduction to Algorithms, Third Edition, The MIT Press, 2009, ISBN: 978-0-262-03384-8


0 Lectures:

2

Labs:

2

Workshops:

0

Research study:

0

Teaching methods

Conventional lecturing and exercises. Case studies. Seminar papers and homework in small groups.





Degree level: BSc

Course:

Probability Theory



ECTS points: 6

Prerequisites:

Course objective:

Students will be able to understand and solve theoretical and practical problems in the field of probability. Student will obtain foundation for understanding methods and models of statistical analysis.

Learning outcomes

The content of the course prepares students for solving practical problems and is gives foundation for understanding methods and models of statistical analysis.



T01: Descriptive statistics. T02: Parameters in descriptive statistics. T03: Random events and its’ features. Operations and relations with random events. Probability (definitions). T04: Conditional probability features. Formulae of total probability, Bayes formulae. T05:One-dimensional discrete random variables. T06: One-dimensional continuous random variables. T07: Parameters of random variables. Moment generating function. Chebyshev’s inequality. T08: Models of discrete distributions. T09: Models of continuous distributions. T10: Limit theorems in probability. T11: Two-dimensional discrete random variables. T12: Two-dimensional continuous random variables. T13: Moments of two- dimensional distributions. T14: Marginal distributions. Conditional distributions. T15: Regression analysis.


P01: Permutation, combinations, variations. P02: Statistical features. P03: Measures of central tendency. P04: Measures of variability. Random events. P05: Probability, conditional probability. P06: Total probability, Bayes formulae. P07: One-dimensional discrete random variables. P08: One-dimensional continuous random variables. P09: Parameters of random variables. P10: Models of discrete distributions. P11: Models of continuous distributions. P12: Two-dimensional discrete random variables. P13: Two- dimensional continuous random variables. P14: Marginal distributions. Conditional distributions. P15: Regression analysis.

Literature/Readings

1. Vuković N., Osnove verovatnoće, FON, Beograd, 2012. 2. Bulajić M., Vukmirović D., Radojiĉić Z., Đoković A., Totić S., Dobrota M., Teorija

verovatnoće zbirka zadataka, FON, 2013. 4. Vuković N., PC statistika i verovatnoća, FON, 2005.








Colloquium 20

Seminar 20


Degree level: Under graduate academic studies

Course:

Decision Theory

Teachers:Suknović M. Milija,Delibašić V. Boris


ECTS points: 5

Prerequisites: /

Course objective

Getting knowledge of multiattribute decision making methods and analysis with the emphesize on real world examples and problems.

Learning outcomes

Student should be able to work with representative decision making methods as well as to develop new decision making models. Students should get theoretical as well as practical skills for working in modern software for decision making.


Theoretical instruction

01: Introduction to decision making. 02: Multi-attribute decision making methods with case studies. 03: IKOR method with case studies. 04: Promethee and Electre methods with case studies. 05: AHP method with case studies. 06: Group decision making. 07: Group decision making case studies. 08: Decision making software 1. 09: v 2. 10: Invited lecture 1. 11: Invited lecture 2. 12: Multi-criteria decision making methods with case studies. 13: Utility theory with case studies. 14: Integrated decision making systems. 15: Group consultations (preparation for the exam).

Practical instruction

01: Basic multi-attribute decision making methods. 02: LDR and IKOR methods. 03: Summarizing of lectures 1. 04: Методе Promethee и Electre. 05: Метода АХП. 06: Модели групног одлучивања. 07: Summarizing of lectures 2. 08: Implementation of decision making methods in Microsoft Excel. 09: Examples of modeling of real world business decision making problems and assignment of students projects. 10: Preparation for project presentation. 11: Presentation of projects 1. 12: Modeling of real world decision making problems in software package. 13: Modeling of multi-attribute utility theory in software package. 14: Modeling of group decision making problems in software. 15: Project presentation 2.

Literature/readings

1. Suknović M, Delibašić B. (2010) Decision Making (in Serbian), Faculty of Organizational Sciences, Belgrade, Serbia.

2. Ishizaka A, Nemery P (2013) Multi-Criteria Decision Analysis: Methods and Software, Wiley. 3. Presentations and materials from web site www.odlucivanje.fon.bg.ac.rs


Lectures: 2 Labs: 2 Workshops: Research studies:

Teaching methods

Teaching is realized by the combination of classic lectures, case studies and invited lectures from experts from industry. Exercises are realized through solving an assignments as well as presentation of software packeges for decision making.


Pre-exam requirements Points Final Exam Points

Project proposal 50

Oral exam 50



Course:

System theory



ECTS points: 6

Prerequisites: none

Course objective The aim of this course is to provide students with the necessary theoretical knowledge of the fundamental concepts, methods and techniques of system theory, and their application for solving practical management and control problems. Learning outcomes The acquired knowledge of the concepts of system theory will enable students to appropriately model and control practical business problems using ICT.



Systems, models and concept of state. State properties and equations of state transition. Dynamics of discrete time and continuous time systems. Linearization and linear models. Reachability, controllability and observability – definitions and properties. Reachability, controllability and observability of discrete time systems. Behaviour of time-varying continuous time systems. Distributions, generalized functions, Dirac and Heaviside functions. Time invariant linear systems. Matrix exponential, diagonalisation, Jordan’s canonical form, block diagram and signal flows graphs. Reachability, controllability and observability of continuous time systems. Introduction to Stability theory. Stability of system state, input- output stability, Lyapunov’s stability. Control and management of systems and feedback. Controllability and canonical forms.


Laplace transform. Inverse Laplace transform. Solving of differential equations. Z transform and inverse Z transform. Solving of difference and recurrent equations. Sampling theorem. Notion of linearity, time invariance, causality. State consistency in continuous and discrete time. Input-output descriptions, system response, linearization. Reachability, controllability and observability of discrete time systems. Matrix exponential, impulse response, state transition matrix and diagonalisation. Jordan’s canonical form, block diagram and signal flows graphs. Controllability and observability of continuous time systems. Phase portrait, systems satability, BIBO stability, Lyapunov’s stability, structural stability.

Lab instruction:

Practical instructions closely follow the lectures. In the course students gain hands-on knowledge and

skills for solving practical problems using selected software packages (Matlab, Mathematica and SciLab).

Literature/Readings

1) B.J. Petrović, System theory (in Serbian) FOS, Beograd, 1998.

2) E. Sontag, Mathematical Control Theory, Springer, 1998.

3) H. Kwakernak, R. Sivan, Modern Signal and Systems, Prentice Hall, 1990.


Lectures:

2

Labs:

2 + 1


Teaching methods

Lectures. In the course students gain hands-on knowledge and skills for solving practical problems using selected software packages (Matlab, Mathematica and SciLab). Project assignments for individuals or small groups.




Oral exam 40



Course:

Systems theory 2



ECTS points: 4

Prerequisites: none

Course objective

The aim of this course is to introduce students to the basic concepts of discrete event systems (DES) characterized by simultaneity, saturation or competition, found in information networks, databases, multiprocessor systems, manufacturing systems, transportation networks, in order to provide students with the ability to manage organizational systems.

Learning outcomes

The acquired knowledge will enable students to model and manage organizational systems using the models and methods of discrete event systems theory.



Examples of organizational discrete event systems (min,+) and (max,+), linear systems, Markov chain optimization. Petri net (PN). Hierarchical, deterministic, stochastic and fuzzy PN. Structural and dynamic properties, reachability. Linear time events graphic. Marker and counter equation, ARMA model, basic equation of state. Calculating cost of production from the event graph. Automata and discrete events systems.

Practical instruction: Laboratory exercises

Solving practical problems using software packages Matlab and NeuroSolutions

Literature/Readings

1) C. G. Cassandras, S. Lafortune, Introduction to Discrete Event systems, Springer, 2007.

2) B. J. Petrović, Uvod u dinamiĉke sisteme diskretnih dogaĊaja, FON, 2002.

3) W.M. Wonham, Notes on Control of Discrete-Event Systems, Department of Electrical and Computer Engineerings University of Toronto, 2002.


Lectures:

2

Labs:

2


Teaching methods








Course:

Introduction to Information Systems

Teacher:Pantelić S. Ognjen,Vučković Đ. Milica,Babarogić S. SlaĎan


ECTS points: 6

Prerequisites:

Course objective

The course is designed to introduce students to the core concepts of information systems and the important aspects of information system development process. Students learn how organizations acquire and process complex information in clear and compelling ways. The course provides a general overview on the implications of information systems on quality of organization processes and competitiveness of the organization itself.

Learning outcomes

Students learn the basic theory of information systems development, its life-cycle processes and phases. Student acquire knowledge related to the understanding of different types of information systems in an organization and their role in today's competitive business environment. The student learns the techniques of business process analysis and data modeling.



Basic concepts of information systems, Information systems architectures, Information systems development models, System analysis techniques, Data modeling, Software and systems engineering standards, CASE tools, IS Implementation, Maintainance of IS, Analytical processing- Decision Support Systems, Artificial Intelligence and Expert Systems, Introduction to e-business, Security of IS, Ethical and social issues in IS, Preparing for exam.


Structured system analysis, Structured system analysis- practical examples, Data Dictionary fundamentals- structure and content, Introduction to data modeling, Logical design of relational database- practical examples, Logical design of relational database- more complex practical examples, Transformation of entity-relationship model into tables- practical examples, Introduction to MS Access tool, Creating tables in MS Access, SQL query language- practical examples, Working with forms in MS Access, Creating reports in MS Access, Preparing for practical tests.

Literature/Readings

1. Rainer, Turban: Introduction to Information systems, DataStatus, 2009 2. Dragana Beĉejski- Vujaklija, Introduction to Information systems, 2007 3. Ognjen Pantelić, MS Access tool guide, FON, 2007 4. Vladimir Zwass, Fondations of information systems, McGraw-Hill, 1998


Lectures:

2

Labs:

1

Workshops:

2

Research study:

Teaching methods

Theoretical lectures, Practical lectures in laboratory, Practical project work in small groups.



Practical paperwork 16 Written exam 60

Test 24


Degree level: Undergraduate studies, the first level

Course:

Introduction to Combinatorial Optimization

Teacher:Čangalović M. Mirjana,Stanojević J. Milan,Mladenović M. Nenad


ECTS points: 5

Prerequisites: Operations Research 1, Operations Research 2

Course objective

Introducing students to basic problems, models and methods of Combinatorial Optimization.

Learning outcomes

Knowledge of how to use specialized models and methods for solving combinatorial optimization problems that are often met in industry, traffic, telecommunication, etc.



Numerical complexity of problems and algorithms. A heuristic approach to problem solving. Notion of the heuristic. Survey of some of most important metaheuristic methodologies. Integer programming. Integral polytopes. Branch and Bound methods. Cuting Plane methods. Branch and Cut methods. Implicite enumeration. Extremal paths in graphs. Maximum Flow problem in a network. Minimum Cost Flow problem in a network. Optimal Matching problem on a bipartite graph. Hamiltonian circuits in graphs. Traveling Salesman problem (TSP). Special and metaheuristics for solving TSP. Optimal Coloring problem on a graph. Special and metaheuristics for optimal coloring of graphs.

Practical instruction: Applications of comercial software packages BARON, CPLEX and CONCORD to solving integer programming models of combinatorial optimization problems studied within theoretical lessions.

Literature/Readings

1. Cvetković D., Ĉangalović M., Dugošija Đ., Kovaĉević-Vujĉić V., Simić S., Vuleta J., Kombinatorna optimizacija, Matematiĉka teorija i algoritmi, DOPIS, Beograd, 1996.

2. Cook W.J. at al., Combinatorial optimization, John Wiley&Sons,Inc., 1998.

3. Korte B., Vygen J., Combinatorial Optimization, Theory and Algorithms, Springer, 2012

4. Vujošević M., Metode optimizacije u inţenjerskom menadţmentu, AINS,FON, Beograd, 2012


Lectures: 2 Labs: 2 Workshops: Research study: 1

Teaching methods

Research studies with mentors and/or classical lessions with computer software applications.




Essay (s) 35 Oral exam 25



Course:

Introduction to Mathematical Programming

Teacher:Vujčić V. Vera,Mladenović M. Nenad,Mihić R. Olivera


ECTS points: 4

Prerequisites:-

Course objective

The course gives an introduction to basic mathematical programming models and methods and related software packages.

Learning outcomes

Students are trained to solve basic mathematical programming problems on the computer.



1. Examples of mathematical programming models of real-world problems. 2. Linear programming. 3. Discrete optimization. 4. Unconstrained optimization. 5. Convex programming. 6. Nonconvex programming. 7. Nonlinear programming methods. 8. Interior point methods for linear programming. 9. Software packages for mathematical programming problems.


Experiments with software packages for mathematical programming on selected problems.

Literature/Readings

1. Zlobec S.., Petrić J., Nonlinear Programming, Scientific Publishers, Belgrade, 1989.

2. Vujĉić V., Ašić M., Miliĉić N., Mathematical Programming, Mathematical Institute of the Serbian Academy of Arts and Sciences, 1980.

3. Nash S., Sofer A., Linear and Nonlinear Programming, McGraw-Hill Companies, Inc., 1996

4. V. M. Tikhomirov, Stories about Maxima and Minima, American Mathematical Society, 1990.



Teaching methods

Classroom lectures/consultations




seminar 35 Oral exam 25



Course:

Introduction to electronic business management

Teacher:Marković M. Aleksandar


ECTS points: 4

Prerequisites: none

Course objective

The primary objective is to identify and discuss the basic concepts of e-business management and characteristics of business systems that operate over the Internet. The aim is also to define the basic processes of e-business, as well as micro-and macro-environmental factors for e-business organization. To define and explain the decisions important for the organizations going towared the e-business and discuss activities in which such decisions are made.

Learning outcomes

To enable students to learn the basic concepts of e-business management. To set the essential theoretical and practical foundation for the further upgrading of knowledge in this area. To provide knowledge and enable students to learn the basic skills needed to manage organizations in the area of electronic business/commerce. To provide answers to the basic questions to be considered in the e-businesss organizations: What is the connection between tradicional and e-business? What are the main characteristics of the organizations in the fields of e-business? Which approach in e-business strategy selection should be adopted? How to invest in e-business? What processes should be a priority for our organization in terms of e-business? Whether to adopt new business models and new revenue models? What changes should be made in the organization to get started with e-business?


Theoretical instruction: The historical development of management concepts. Basic concepts and definitions of management. Phases of management and management levels: strategic, tactical and operational. Changes in management caused by using the Internet. Impact of the Internet on the stages of the process control and management levels. Introduction to e-business and e-commerce. Basics of e- commerce. Infrastructure of e-business and e-business infrastructure mangement. E-business environment: micro-and macro-environment and key environmental factors. E-business strategy. Intranet and Extranet and its use in business functions.


Discussions with students. Examples, case studies, analysis.

Literature/Readings

1. Chaffey, Dave, E-Business and E-Commerce Management, (Part I), Pearson Education Limited, Essex, UK 2009.

2. Marković, Aleksandar, E-business management-teaching materials (e-format), http:// mep.fon.bg.ac.rs, FOS, Belgrade, 2013.



Teaching methods

Lectures, discussions, case studies, exercises, analysis of specific examples from practice



Participation in class 5 Essays/projects 15

Colloquia 30 Oral exam 50



Course:

Introduction to neural networks

Teacher:Petrović J. Bratislav,Radojević Dragan


ECTS points: 4

Prerequisites: none

Course objective

The aim of this course is to introduce students to the basic theoretical concepts, architectures and learning rules of neural networks and learning rules, as well as to analyze their properties (using both the mathematical as well as the systems approach) in order to provide students with the ability to solve practical problems of management in organizational sciences.

Learning outcomes

The acquired knowledge will enable students to model and simulate organizational systems using neural networks and information and communication technologies.



Basic concepts, functioning and history of artificial neural networks. Main types of neural networks. Learning rules, activation functions and weight functions. Tuning and optimizing network performance. Network architecture. Perceptron. Single-layer linear network. Data capturing and preparation. Preparing for learning. Learning in neural networks and learning algorithms. Mean square error. LMS algorithm, convergence. Multilayer linear networks. Backpropagation algorithm. Specification of network architecture. Improving convergence speed. Levenberg-Marquardt algorithm. Network testing. Existence of minimum and maximum. Newton method, method of steepest descent, conjugate gradient. Associative learning. Supervised Hebbian learning. Implementing neural networks. Recurrent networks. Concepts of stability. Hopfield network. Disadvantages and limitations.

Practical instruction: Laboratory exercises

Solving practical problems using software packages Matlab and NeuroSolutions

Literature/Readings

1) S. Haykin, Neural Networks: A Comprehensive Foundation, MacMillan, 1994.

2) M.T. Hagan, H. B. Demuth, M. Beale, Neural Network Design, PWS Boston, 1999.

3) J. C. Principe, N. R. Euliano, W. Curt Lefebvre, Neural and Adaptive Systems: Fundamentals through

Simulations, Wiley, 2000.


Lectures:

2

Labs:

2


Teaching methods








Course:

Introduction to optimal control and game theory

Teacher:Petrović J. Bratislav,Gajić R. Zoran


ECTS points: 4

Prerequisites: none

Course objective The course is designed to introduce students to the basic concepts, principles, models and techniques of game theory and the possibility of their application in modeling and analyzing strategic interaction in the complex and interactive business environment.

Learning outcomes Students will be trained in strategic and analytical thinking and application of concepts of game theory in modeling and solving real-world problems.



Modelling and optimality criteria. Calculus of variations, dynamic programming and Pontryagin's maximum principle. Numerical methods for solving optimal control. Optimal control of continuous/discrete, deterministic/stochastic, linear systems with quadratic criterion. Matrix game, non- cooperative and simultaneous games. Dynamic games (continuous and discrete time): Stackelberg, Nash and Pareto strategy. Application of the game theory in economy, organizational and financial engineering.


Practical instructions closely follow the lectures. In the course students gain hands-on knowledge and skills for solving practical problems using selected software packages (Matlab, Mathematica and SciLab).

Literature/Readings

1) M. I. Zelikin, Control theory and optimization I: Homogeneous Spaces and the Riccati Equation in the Calculus of Variations, Springer, 2000.

2) R. Branzei, D. Dimitrov, S. Tijs, Models in cooperative game theory: crisp, fuzzy, and multi-choice games, Springer, 2005.



Teaching methods








Course:

Introduction to fuzzy logic

Teacher:Petrović J. Bratislav,Radojević Dragan


ECTS points: 4

Prerequisites: none

Course objective The aim of this course is to provide students with the necessary theoretical knowledge of the fundamental concepts, methods and techniques for modeling uncertainty, imprecision, incompleteness and their application for solving practical business problems.

Learning outcomes The acquired knowledge of the concepts of fuzzy logic will enable students to select tools and appropriately model practical business problems in organizational systems using ICT.



Fundamental concepts, classical and fuzzy sets. Operations on fuzzy sets. Interval and fuzzy arithmetic. Fuzzy relations. Fuzzy relational equations. Classical logic and a motive for generalization. Multi-valued and [0,1]- valued logic. Fuzzy logic. Fuzzy inference systems, Mamdani and Sugeno systems. Fuzzy controllers and fuzzy control systems. Approximate reasoning. Fuzzy decision making. Fuzzy pattern recognition. Fuzzy search. Fuzzy time series.


Practical instructions closely follow the lectures. In the course students gain hands-on knowledge and skills for solving practical problems using adequate software packages (Matlab, Mathematica and SciLab).

Literature/Readings

1) D. Radojević, B. Petrović, Uvod u fazi logiku i sisteme, lectures, at www.labsys.fon.bg.ac.rs.

2) G. J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic– Theory and Applications, Prentice Hall, 1995.

3) G. Bojadzijev, M. Bojadzijev, Fuzzy logic for Business, Finance, and Management, Second edition, World Scientific, 2007.



Teaching methods



Course:

Supply Chain Management 1

Teacher:Vasiljević V. Dragan,Stanojević J. Milan


ECTS points: 4

Prerequisites: Logistics or some of the courses of management science

Course objective: To introduce the students with the role of supply chains in contemporary business, and with the basic methods of demand planning and management in supply chains.

Learning outcomes: Basic theoretical and practical knowledge and skills for management of processes and flows in supply chains.



T-01: Course introduction.

T-02: Traditional and JIT sourcing.

T-03: Logistics and supply chain integration.

T-04: Definition and basic features of SCM concept.

T-05: Collaboration in supply chains: definition, role and levels.

T-06: Evolution of SCM.

T-07: The bullwhip effect: definition and causes.

T-08: Theoretical foundations of location problems in supply chains.

T-09: Demand and inventory management in supply chain.

T-10: Optimization in supply chain.

T-11: Basics of performance measurement in supply chains.

T-12: Resource planning in supply chains.

T-13: Distribution strategies.

T-14: Control test.

T-15: Presentation of term papers. Practical instruction:

P-01: Supply chain manager.

P-02: Types of supply chains and their

demonstrations.

P-03: Methods of transportation management in

supply chains.

P-04: The Quick Response (QR) concept.

P-05: The Efficient Consumer Response (ECR)

concept.

P-06: Test 1.

P-07: Simulation of bullwhip effect in supply

network. Literature/Readings:

1. Vasiljevic D., Jovanovic B., Logistics and Supply Chain Management, ISBN 978-86-7680-150-3, FOS,

Belgrade, 2008. (in Serbian) 2. Chopra, S., Meindl, P., Supply Chain Management: Strategy, Planning, and Operations, Pearson

Education, New Jersey, 2004. 3. Drezner Z., Hamacher H., Facility Location - Applications and Theory, Springer-Verlag, Berlin-

Heidelberg, 2002. The number of class hours per week Other classes


Teaching methods: Ex cathedra teaching, interactive teaching methods (creative workshops and case studies), practical and lab exercises.





Tests 30

Term paper 15

Method of knowledge evaluation:

Grades 5 6 7 8 9 10

Points [0-55] [56-65] [66-75] [76-85] [86-95] [96-100]


Degree level: Bachelors study

Course:

Project Management

Teacher:Obradović LJ. Vladimir,Martić M. Milan


ECTS points: 5

Prerequisites:

Course objective

The acquisition of scientific theoretical and practical knowledge of Project Management, necessary for successful application and implementation on various projects and programs.

Introduction as well as utilization of modern methods and techniques of Project Management.

Learning outcomes

Improving students’ competences of practical application of technical knowledge concerning: time management, cost management, resources management, quality and risk management, as well as communications and contract management in the process of preparation and implementation of projects.



Concept and types of projects. The concept of project management. Organization of project management. Human resource management in the field of project management. Contracting management. Quality management in the field of project. Project risk management. Managing communications in the project. Managing change in the project. Project planning. Monitoring and control of the project. Reporting system concerning the implementation of the project. Standard computer programs for project management. Managing by projects. Project organizations. Program management. Multi-project Management.


Structural diagrams - WBS and OBS. Structural diagrams - RACI matrix. Method of key events. Gantt chart. Priority method. Analysis of the structure of a network diagram. Time analysis method CPM. Time analysis method PERT. Method of resource leveling. Cost Analysis. Actual values method. Method PRINCE 2. Microsoft Project.

Literature/Readings

1. P Jovanović., Project Management, FON, Belgrade, 2006

2. H Kerzner, "Project Management", VIII edition, John Wiley & Sons, New Jersey 2003 The number of class hours per week Other classes:

Lectures:

2

Labs:

2


Teaching methods

Auditory, illustrative and demonstrative, verbal and textual, practical methods.







Course:

Risk management in e-business projects

Teacher:Despotović-Zrakić S. Marijana,Bogdanović M. Zorica,Barać M. Dušan,Labus B. Aleksandra


ECTS points: 5

Prerequisites:

Course objective

The aim of this course is to introduce concepts of project management information systems, as well as the methods and models for risk management in e-business software projects.

Learning outcomes: Students gain theoretical and practical knowledge for project management in IT. Students mastered common techniques, methods and concepts for IT project management and risk management.


Theoretical instruction: Architecture and paradigms in development of e-business systems. Standards in development of e-business systems. E-business project management. Agile methods for IT projects management. IT risks. Technical and organizational aspects of IT risks. Methods and techniques for the risks identification and assessment. Risks monitoring and reporting. Learning from risks. Methods of risks management in development of information systems. Risks management in projects of information systems in a distributed environment. Business process analysis. Modeling business processes. Business Analysis. MSF methodology for risk management. Principles of web applications security. Risk management in mobile environment. COBIT framework for information technology management. ITIL framework for IT service management. Management of information security using the ISO/IEC 27000 series of standards. Creating a security policy. Business Continuity Management. Incident management. Planning system recovery. The methodology and techniques of IT audit. IT audits.

Practical instruction: Development of Risk management plan. IT project management using MS Project. Managing software development projects using Redmine tools. Business process modeling using PowerDesigner tool. The introduction of standards for information security management. Development of risk management plan. Develop a plan for business continuity. Develop a plan for incident management. Application CAATT tools and techniques and IT audit. Case studies - IT projects.

Literature/Readings

1. E-resources, available at www.elab.rs 2. M. Despotović, Upravljanje razvojem softvera u .Net okruţenju, Info M 6-7, str. 10-16, Beograd,

2003. 3. Brewer J, Dittman C, Methods of IT Project Management, Prentice Hall, 2010 ISBN:

9780132367257

4. Hall J, Information technology auditing and assurance, South-Western Cengage Learning, 2011, ISBN: 9780538469302

5. M. E. Whitman, H.J. Mattord, Principles of information security, Australia: Thomson Course Technology 2003. ISBN: 978-1111138219

6. Tipton H., Krause M. Information Security Management Handbook, 6th Edition, Auerbach publications, 2007

7. Colisto N. The CIO Playbook: Strategies and Best Practices for IT Leaders to Deliver Value, Wiley, 2012

8. Kouns J., Minoli D. Information Technology Risk Management in Enterprise Environments, Wiley, 2010



Teaching methods





Seminar paper 40


Degree level: Master

Course:

Software Project Management

Teacher:Đurić O. Dragan,Devedţić B. Vladan


ECTS points: 6

Prerequisites: Data Structures and Algorithms

Course objective

Mastering software project management techniques and practical skills.

Learning outcomes

Students’ ability to organize software projects, in technical sense and as an everyday work in a software development company.



Software process. Iterative and incremental process examples. Agile software process. Software process standardization. Software Metrics. COCOMO and FPA metrics. Chidamber-Kemerer metrics. Organizational aspects of software project management. Success and failure factors. Study example.


Labs. Other forms of teaching. Research study work. Work with tools for automating software builds. Work with tools for software versioning. Work with tools for software metrics. Practical project.

Literature/Readings

• Digital learning resources available on the course CD. • Examples of practical software projects. • Open source software frameworks and tools, as well as their documentation and useful tutorials are

freely available on the Web. • Labs consists of practical work on students’ own projects under the supervision of the assistants.


– Lectures:

2

Labs:

2

Workshops:

-

Research study:

–

Teaching methods









Course:

Physical Project of IS in Selected Software Environment (project)

Teacher:Aničić M. Nenad,Babarogić S. SlaĎan



Prerequisites: Analysis and Logical Design of IS (project)

Course objective

The goal of this course is to train students to develop and implement real IS in selected modern software environment in accordance with object-oriented specification of IS.

Learning outcomes

Students will extend their knowledge by implementing an information system in an emerging systems environment, using components and patterns.



Introduction. Explanation of software architecture elements that needs to be implemented. Overview of J2EE development environment. Advanced J2EE development environment technologies. Overview of .NET development environment. Advanced .NET development environment technologies.


Determining visibility, creating detailed class diagrams. Organizing UML packages of project and implementation models. Persistent framework design using patterns. Mapping model elements into program code. Defining class definition which bases on detailed class diagrams. Defining methods based on interaction diagram and statechart diagram. Implementation in J2EE or .NET environment. Implementation.

Literature/Readings

- Basic Literature:

1. Materials and scripts from lectures and labs, Laboratory for Information systems, FOS

2. e-Presentations on course site pisbp.fon.bg.ac.rs

- Additional Literature:

Larman C., Applying UML and Patterns-An Introduction to Object-Oriented Analysis and Design and Iterative Development, 3rd ed., Prentice Hall, 2004.



Teaching methods

Students will use modern development environment for implementation of the project which bases on previous courses. In first five weeks theoretical lectures consider not just basic elements of software architecture that needs to be implemented, but also gives a review on two current, modern software development environments. Next 9 weeks students are working on IS implementation and in defined control points of the project they meet lecturer for revision.



Project development 100



Course:

Financial Management and Accounting

Teacher:Ţarkić-Joksimović A. Nevenka,Benković S. SlaĎana,Barjaktarović-Rakočević M. SlaĎana,Kneţević P. Sneţana


ECTS points: 6

Prerequisites:

Course objective

Instructing students to basic concepts and methods of financial management such as place of financial function in organization, system of financial management in organization, financial markets, financial planning, financial analysis, investment policy and investment decisions, as well the concept and content of accounting, specifics of double bookkeeping, bookkeeping of costs and expenditures, bookkeeping and inclusion of income, methods for calculating periodic results, distribution of periodic results. The stress will be on basic financial and accounting concepts and categories in order of understanding the financial and accountant manager’s role in organization.

Learning outcomes

Content of this course qualifies students for making financial and accounting decisions, due to of understanding key financial and accounting problems in organization, which is the basis for solving the practical management problems throughout applying of financial and accounting management concepts and methods. Course structure and content


Financial function in enterprise. Financial management system in enterprise. Institutional and business environment. Financial markets. Financial planning. Financial analysis. Investment policy. Risk and investment decisions. Current asset management. Liquid asset management. Short-term financing. Long- term financing. Financing policy. Dividend policy.


Term and scope of financial accounting. Bookkeeping records. Assets, equity and liabilities bookkeeping. Costs and expenses bookkeeping. Revenues bookkeeping. Pre-closing entries and closing entries.

Literature/Readings Ţarkić Joksimović Nevenka, SlaĊana Benković, Miloš Milosavljević: Finansijski menadžment, Fakultet organizacionih nauka , Beograd, 2013.

Ţarkić Joksimović Nevenka, Bogojević Arsić Vesna: Računovodstvo, Fakultet organizacionih nauka, Beograd, 2013.

Ţarkić Joksimović Nevenka, Bogojević Arsić Vesna, Benković SlaĊana, Šikanjić Branko, Zbirka zadataka iz računovodstva, Fakultet organizacionih nauka, Beograd, 2010.

Brigham E: Financial Management: Theory & Practice, Cengage Learning, 2013.

Brigham E, Houston J: Fundamentals of Financial Management, Cengage Learning, 2009.

Titman S, Martin J, Keown A: Financial Management: Principles and Applications, 11th ed., Prentice Hall, 2010.



Teaching methods

Teaching is conducted through lectures, exercises and consultations. Students are actively involved in the learning process through interactive discussions, exercises, homework, case studies and workshops.



Written exam 80

Oral exam 20



Course:

French for specific purposes 1

Teacher:Cakeljić R. Vesna


ECTS points: 2

Prerequisites: B1 level of French language competencies (CECRL).

Course objective

Internalizing the basics of Business French as well as the vocabulary related to the fields of Management and Organization, Information systems and Technologies. Developing language competencies and communication skills in French. Consolidation of major elements of grammar (uses of the subjunctive, the present participle and its uses, direct and indirect object pronouns, etc.). This course will focus on understanding French social and economic issues to enable students to engage with native speakers in the business context.

Learning outcomes Students are given input to enable them to engage in basic types of communicative situations in French within the domain of their respective future professions (the corporate world) as well as for creating functional tools necessary for employment (CV and motivation letter). Students have gained insight into the common business practices of French companies and internalized the specific business vocabulary. They are able to participate in basic professional conversations on topics related to employment, marketing, management, advertising, description of companies, products or services relevant to their specific career, as well as travelling for business. They have also consolidated and expanded grammatical and syntactical competence. By the end of the module, students should be able to perform at Level B2 of the Common European Framework.



Semester 1: Acteurs économiques. T-01: Types de travailleurs. T-02: Une journée de travail. T-03: Types et rôles de l'entreprise. T-04: Fiche d’identité d’une entreprise. T-05: Services bancaires. T-06: Lettre commerciale. T-07: Droits du consommateur. T-08: Types de revenus. T-09: Rôle de l'Etat. Créateurs d’entreprises. T-10: Profil du créateur. T-11: Recherche de capitaux. T-12: Lieu d'implantation; écrire efficacement. T-13: Choix de société. T-14: Formalités de création d'une entreprise; T-15: Contenu d'un e-mail. Semester 2: Ressources humaines. T-1: Contrat de travail. T-2: Profil de manager; Offre d'emploi. T-3: CV, Lettre de motivation. T-4: Entretien d’embauche. T-5: Méthodes d'organisation du travail. T-6: Réunion de travail. T-7: Compte rendu. T-8: Droits de salariés. Marketing. T-09: Étude du marché. T-10: Questionnaire d’enquête. T-11: Définition du produit, prix, marque, conditionnement. T- 12: Méthodes et formes de distribution, de vente. T-13: Moyens de communication. T-14: Rôle du vendeur. T-15: Techniques de vente.


Semester 1: P-01: Interrogation directe. P-02: Diverses manières de poser une question. P-3: Article indéfini des, préposition de. P-4: Jeu de rôles. P-05: Pronoms compléménts le, la lui, pronoms relatifs simples. P-6: Mise en page d’une lettre d’affaires. P-07: Pronoms relatifs simples, mots de liaison. P-8: Réclamation. P-09: Forme passive. Bilan de compétences. P-10: Passé composé/imparfait. P-11: Articles définis, indéfinis, partitifs. P-12: Indicateurs de temps; courriel. P-13: Pronoms y et en; jeu de rôles. P-14: Orthographes de certains verbes au présent. P-15: Rédaction d’un e-mail. Bilan de compétences.

Semester 2: P-1: Pronoms relatifs composés. P-2: Hypothèse; e-mail. P-3: CV et lettre de motivation. P-4: Simulateur d’entretiens d’embauche en D3. P-5: Futur simple; futur antérieur; discussion. P-6: Pronoms

et adjectifs indéfinis. P-7 Jeu de rôles. P-8: Subjonctif. Bilan de compétences. P-09: Place des pronoms compléménts; impératif. P-10: Réaliser un questionnaire d'enquête. P-11: Comparaison; rédiger un rapport; e-mail. P-12: Prépositions et adverbes de lieu; rédiger un compte rendu. P-13: Discours rapporté (au présent). P-14: Infinitif, complément du verbe. P-15: Jeu de rôle. Bilan de compétences.

Literature/Readings

− Jean-Luc Penfornis: Affaires.com, Paris, CLE International, 2012.

− Vesna Cakeljić: Lexique des affaires, Ključne reči menadžmenta i informatike, Beograd, FON, 2013.

− Vesna Cakeljić: Management.com, Prosveta, Beograd, 2008.


Lectures:

1

Labs:

1


Teaching methods

Interactive and communicative approach, encouraging students to participate in group discussions and exercises; case studies and presentations; the use of audio/video/web material.





Colloquium 20



Course:




ECTS points: 3

Prerequisites: completion of the course and final exam in French for specific purposes 1

Course objective

The further consolidation and extension of existing language skills (acquired during the course in French for specific purposes 1) as well as specific vocabulary used in leading business in a French/Francophone context. Further reinforcement of students’ knowledge about the world of French companies and new technologies. Providing insight into the French culture and business ethics with the aim of developing students’ intercultural communicative competence. Learning outcomes

Students are given input to enable them to participate in interactive communication within the French business environment, in situations ranging from informal conversation to formal interviews, negotiations or presentations, especially for professional correspondence (mails, letters, reports, etc.). By the end of the module, students will have: consolidated and expand grammatical and syntactical competence (hypotheses, passive form, etc.), developed competence in a broad range of complex language tasks across a wide variety of business contexts, and acquired the specific terminology used in the business world. They should be able to perform at Level C1 of the Common European Framework.



Semester 1: Correspondance professionnelle. T-01: Prise de contact, partenaires de l'entreprise. T-02: Voyage d’affaire. T-03: Commande en ligne. T-04: Service clientèle: livraison. T-05: Réclamations. T- 06: Règlement de facture. T-7: Mécanisemes d'assurance. T-8: Déclaration de sinistre. Résultats et tendances. T-9: Secteur d'activité. T-10: Rapport sur l’évolution des ventes. T-11: Analyser les résultats de l'entreprise. T-12: Bilan d'entreprise; rôle de la comptabilité. T-13: Comptes de la nation: données chiffrées d'une ville, d'un pays. T-14: Commerce extérieur. T-15: Libre échange et protectionisme. Semester 2: T1 – T15 : Gros plan sur : acteurs économiques, créateurs d’entreprises, ressources humaines, marketing, etc. Aktuelne teme iz sveta poslovanja i novih tehnologija obraĊuju se uz pomoć video zapisa i intervjua: génération numérique, emploi des jeunes, télétravail, commerce en ligne, technologies numériques mobiles, etc.


Semester 1: P-01: Différents façons de demander. P-02: correspondance par e-mails. P-03: Exprimer la condition. P-04: Exprimer la cause. P-05: Jeu de rôles. P-06: Exprimer la conséquence; écrire une lettre. P-7: Exprimer le but. P-8: Bilan de compétences. P-9: Discours rapporté (au passé). P-10: concordance des temps. P-11: Adverbes de quantité; concession. P-12: Exprimer la concession. P-13: Exprimer l'opposition. P-14: Indicatif ou subjonctif. P-15: Bilan de compétences. Semester 2: P1 – P15 : Entraînement : Diplôme de Français professionnel B2/C1 (CCIP) et DELF Pro B2. Compréhension écrite et connaissance du monde des affaires ; compréhension orale et expression écrite.

Literature/Readings

− Jean-Luc Penfornis: Affaires.com, Paris, CLE International, 2012.




Lectures:

1

Labs:

1


Teaching methods

Interactive and communicative approach, encouraging students to participate in group discussions and exercises; case studies, jeu de rôles; the use of audio/video/web material.





Colloquium 20



Course:




ECTS points: 4

Prerequisites: completion of courses and final exams in French for specific purposes 1 and 2

Course objective

The main objective of French for academic purposes (Français sur objectifs universitaires) as a new university module, is to facilitate the linguistic integration and the academic success of foreign students in French higher education, whether in France or abroad, in the context of mobility in French-speaking countries, and reinforcement of the general knowledge pertaining to the French culture, the university system and student life in France. The goal of this course is to build on students’academic

Learning outcomes

At the completion of the course, students will have developed the essential language skills necessary for integration into French communities of higher education (universities and Grandes écoles in France). They will be able to: identify the linguistic specificities inherent to French academic discourses, use academic listening strategies, speak with fluency using basic and complex sentence structures, make oral presentations, acquire and use new academic vocabulary in the field of their future professions. They are able to understand lectures given in French, to take notes, write reports, term papers and other academic papers. The students are familiarized with the structure of the French university system as well as the lives of students studying in France.



T-01: Rechercher un emploi. T-02: Poser sa candidature. T-03: Se présenter pour un entretien. T-04: Travailler: s’informer sur le travail. T-05: Réussir sa carrière. T-06: Aménager le temps de travail. T-07: Découvrir l’entreprise. T-08: L’organisation de l’entreprise: présenter / analyser. T-09: Différentes formes juridiques des entreprises. T-10: Création d’entreprise: se mettre à son compte; implanter une entreprise. T-11: Diriger: être patron, chef; prendre des décisions. T-12: Organiser: un voyage d'affaire, un lieu de travail. T-13: Produire; espionner et contrefaire; informatiser et robotiser. T-14: Courir / couvrir des risques; connaître environnement / partenaires. T-15: Commerce extérieur / libre échange et protectionisme.


P-01: Organigramme; consulter des petites annonces; téléphoner. P-02: Rédiger un CV et une lettre de motivation. P-03: Simulation d’entretien de recrutement. P-04: Expression de la comparaison; remplir une questionnaire. P-05: Emploi des participes; participe présent. Bilan de compétences P-06: Expression du temps. P-07: Expression de l’opposition; bilan de compétences. P-08: Présenter sa faculté / une entreprise serbe. P-09: Emploi du subjonctif. P-10: Exprimer l’hypothèse. P-11: Étude de cas. P-12: Expression du lieu. P-13: Lexique de l'informatique. P-14: Bilan de compétences. P-15: Indicatif ou subjonctif. Bilan de compétences.

Literature/Readings

− Jean-Luc Penfornis: Vocabulaire progressif des affaires, Paris, CLE International, 2004.




Lectures:

1

Labs:

1


Teaching methods

Interactive and communicative approach, encouraging students to participate in group discussions and exercises; case studies and presentations; the use of audio/video/web material.





Colloquium 20



Course:

Heuristic methods

Teacher:Mladenović M. Nenad,Čangalović M. Mirjana,Stanojević J. Milan


ECTS points: 6

Prerequisites: Operational research 1

Course objective

Introducing students to modern heuristic methods for solving hard optimization problems..

Learning outcomes

Students will be capable to use basic principles of heuristic approaches to solve real-life problems and train for application of some of the general heuristic methodology.



Elements of computational complexity. The classes P and NP. Basic principles of heuristic approach for solving problems. The term heuristics. Examples of special heuristics. Basic principles of general heuristic methodology. The term environment. The principle of local search. Avoiding the pitfalls of local extremes. The general scheme of general heuristic methods. Simulated annealing. Tabu search. Variable Neighbourhood. Genetic algorithms. Some applications of general heuristics. Backpack problem. The traveling salesman problem. The problem of graphs coloring. The problem of continuous global optimization.


The use of existing software packages for heuristic problem solving combinatorial and continuous optimization.

Literature/Readings

1. Cvetković D., Ĉangalović M., Dugošija Đ., Kovaĉević-Vujĉić V., Simić S., Vuleta J., Kombinatorna optimizacija, Matematiĉka teorija i algoritmi, DOPIS, Beograd, 1996. (In serbian)

2. Gendreau M., Jean-Yves P. (Ed.), Handbook of Heuristics, Springer, 2010.

3. Günther Z., Roland B., Michael B., Metaheuristic Search Concepts, Springer, 2010.



Teaching methods

Mentoring and / or the classic way with the use of computers







Course: Programming 3

Teacher: Vladan B. Devedžić, Jelena M. Jovanović, Bojan B. Tomić, Zoran V. Ševarac, Dragan O. Đurić Course status: Elective

ECTS points: 4

Prerequisites:

Course objective

Mastering programming languages, tools and techniques that are trendy in software development.

Learning outcomes

Students' ability to develop programs at an advanced level using programming languages whose popularity grows and using appropriate software programming environments.


Theory teaching Overview of basic and advanced concepts in programming using selected programming languages. These selected programming languages are not permanent - the basic idea is to monitor current programming trends and the popularity of individual programming languages, and accordingly, if necessary, the languages studied under this subject will also be changed accordingly. Working with program libraries and appropriate programming environments dynamically tracks selected programming languages, their paradigms, their application focus and their development. Practical classes: Exercises (in computer laboratories) Introduction to the use of various software development tools using selected programming languages. Creating programs that illustrate basic work using these languages. Repetition exercises 1. Creating programs that illustrate advanced work using these languages. Repetition exercises 2. Creating applications using these languages. Repeat exercises 3. Preparation for exam 1. Preparation for exam 2. Preparation for exam 3.

Literature/Readings

Programming is not learned from books. Only stand-alone practical work on a computer with regular monitoring of teaching and consulting with teachers (or any other experienced programmer) can lead to a successful mastering of programming. Those who insist on any kind of textbook can use any book that describes in detail the programming languages that are being studied in this subject. Supplementary literature: a software CD and solved examples, as well as a site of articles with numerous links to resolved cases.

The number of class hours per week Other classes:-

Lectures: 2 Labs:2 Workshops:2 Research study:-

Teaching methods

Lectures: The teacher programmable on the computer, students follow and discuss the details of the program with the teacher. Exercises: in the laboratory, students themselves program under the guidance of an assistant.



colloquium 0-100 exam on computer 0-100



Course: Internship

Teacher: All teachers on the subject Course status: Required

ECTS points: 2

Prerequisites:

Course objective Training students for independent research and professional work in identifying and solving specific tasks in the field of study programs, in real-life conditions and / or in research laboratories and centers.

Learning outcomes

Acquiring experience and mastering skills in using, deepening and enriching acquired theoretical and practical knowledge to identify and solve specific issues and tasks that arise in the real system.

Course structure and content Elements of the project task; Defining the purpose and task of the research; Determination and description of the basic problem through the elaboration of key theses; Basic methods, techniques and instruments for realization of the project of professional practice - selection of methods appropriate to the project task and foreseen empirical research; The basic elements of the presentation of the results of the research - the principles of a successful presentation and various forms and characteristics of individual forms, for example the contents of a written document, oral, electronic presentation; Defining the specific project task of the professional practice for each student - the goals and tasks, the obligations of the student and the obligations of the organization (if the project is realized in a specific organization), the manner of work, the form and content of the final report. The number of class hours per week Other classes:-

Lectures: Labs: Workshops: Research study:20

Teaching methods Application of different methods of research, consultations (individual and group). Application of different teaching methods with practical work.



seminary work 50 written exam 50



Course: Final Paper

Teacher: All teachers on the subject Course status: Required

ECTS points: 7

Prerequisites:

Course objective The goal of designing and defending the final work is that the student shows the ability to independently effectively and efficiently solve the set of a more complex problem within the selected study program of the first cycle of academic education

Learning outcomes

By elaborating and defending the final work, students who have completed their studies acquired the competences envisaged in the study program, i.e. the student has the necessary academic theoretical and practical knowledge and skills in the selected field, knows in the academic environment a widely accepted methodology for solving complex problems and is able to apply them independently and creatively in solving the problems that will arise in practice. The student is trained for further training while working in the profession by following appropriate professional literature, to cooperate with the team in solving complex problems, both locally and globally.


In general, the content studied in the final work depends on the selected study area and basically represents the integration of the knowledge and skills listed in the subjects that cover the selected study area. The first part of the Introduction describes the needs in the field of research interest, the most important results so far to meet these needs, the description of a specific problem and why it is worth exploring, the goals that are sought to be achieved by solving the problem. The second part of the Introduction contains a shorter review of the proposed approach to the solution of a specific problem, and the third contains a further description of the structure of the final work. The second chapter contains an overview of the situation in the field of special interest research. The third chapter presents the part of the world that is the subject of study and finds a distorted problem in that world. The fourth chapter contains a methodology for solving the problem. Chapter 5 illustrates the solution to the problem, ie the results of the research and the discussion of specific issues. A special chapter contains the Conclusion, ie the summary on solving the problem, the main results that have occurred during the research and their discussion. Finally, Literature is the complete list of sources that are cited in the paper

The number of class hours per week Other classes:-

Lectures: Labs: Workshops: Research study:20

Teaching methods Upon acceptance of the application of the final work, the candidate with the supervision of the mentor approaches the creation of the same. Preparation of the final work should be carried out in accordance with the plan of realization agreed with the mentor. The candidate in the laboratory and / or on the field independently works on the practical aspects of the problem being solved. In consultation with the mentor, he / she checks the work plan, as needed, in terms of the elements it contains, the dynamics of the realization or additional sources.



access work 50 Final paper 50