module specification - university of leicesterapply the basic methods and algorithms for data...

Module Specification

No. Assessment Description Weight % Qual Mark Exam Hours Ass't Group Alt Reass't

001 Coursework 100

Period: Semester 2Occurence: A15Coordinator: Bogdan GrechukMark Scheme: PGT Mark Scheme

Academic Year: 2015/6Module Level: PostgraduateScheme: PGDepartment: MathematicsCredits: 60

Intended Learning OutcomesConstruct, implement and complete an independent programme of research in a way that demonstrates an understanding ofthe concepts and methodologies appropriate to a financial topic. Explain the purposes and significance of their research andplace it in the context of existing literature and industry practice.The student will establish the lines of enquiry to be followed and produce a final thesis on this planned work. Students willproduce a written report on a substantial piece of financial mathematics or computation which will require use of library andother external resources. This will describe the mathematics learned, presenting arguments and solutions in a coherent andlogical form. Students will give an oral and visual presentation to a group of peers and staff."

Teaching and Learning MethodsThis will largely be through independent study with directed activitly led by the project supervisor. Students will be required to record their weekly supervision meetings as well as attend department and univesity seminars. "

Assessment MethodsFinal assessment will be from a combination of final oral presentation and written thesis. Marks are also available forparticipation.

Pre-RequisitesCompleted 120 credits of MSc level mathematics.

Co-Requisites

Excluded Combinations-

LecturesSeminars

Practical Classes & WorkshopsTutorials

FieldworkProject Supervision

Guided Independent Study 440Demonstration

Supervised time in studio/workshop 10Work Based Learning

PlacementYear Abroad

Total Module Hours 450

Student Workload (hours)

MA7002 Individual Project

Last Published: 22 May 2018



001 Continuous Assessment (Final) 100

Period: Semester 2Occurence: ACoordinator: Andrey MorozovMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe student is required to demonstrate ability to gain information from a scientific paper and from a scientific talk and skills topresent a scientific problem.

Teaching and Learning MethodsProblem classes, guided reading.

Assessment MethodsMarked oral presentations, continuous assessment

Pre-Requisites-

Co-Requisites-


LecturesSeminars




Supervised time in studio/workshopWork Based Learning

PlacementYear Abroad 0



MA7003 Research Presentation




001 Coursework (Final) 100

Period: Semester 2Occurence: A15Coordinator:Mark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe student will establish the lines of enquiry to be followed and produce a final thesis on this planned work. Students willproduce areport in LATEX ona substantial piece ofmathematics which will require use oflibrary andother external resources. This willdescribe the mathematics learned, presenting arguments and solutions in a coherent and logical form. Students will give anoral and visual presentation to a group of peers and staff

Teaching and Learning MethodsThis will largely be through independent study with directed activitly led by the project supervisor and programme director.Studentswill be required to record their weekly supervision meetings aswell as attend department and univesity seminars.

Assessment MethodsAssessment will be continous through seminar series log, weekly meetings with supervisor, and two interim presentationsFinalassessment will then form a combinaiton of final oral presentation and written thesis.

Pre-Requisites

Co-Requisites


LecturesSeminars








MA7007 MRes Research Project




001 COURSEWORK (Final) 100

Period: Semester 1Occurence: ACoordinator:Mark Scheme: PGT Mark Scheme


Intended Learning OutcomesAt the end of this module, students should be able to demonstrate knowledge and understanding of the chosen topic studiedin this reading module, and have communicated this through seminar discussions, writtenwork and an oral presentation.

Teaching and Learning MethodsSeminars, guided reading, problems/project.

Assessment MethodsSeminar, written problems/project, oral presentation.

Pre-Requisites

Co-Requisites


Lectures 22Seminars








MA7008 ADVANCED READINGS IN MATHEMATICS




001 COURSEWORK (Final) 100

Period: Semester 2Occurence: ACoordinator:Mark Scheme: PGT Mark Scheme


Intended Learning OutcomesAt the end of this module, students should be able to demonstrate knowledge and understanding of the chosen topic studiedin this reading module, and have communicated this through seminar discussions, written work and an oral presentation.

Teaching and Learning MethodsSeminars, guided reading, problems/project.

Assessment MethodsSeminar, written problems/project, oral presentation.

Pre-Requisites

Co-Requisites


Lectures 22Seminars








MA7009 ADVANCED READINGS IN MATHEMATICS




001 Examination (Final) 80 2002 Computer Practicals 20003 Examination 100 2 Y

Period: Semester 2Occurence: ACoordinator: Emmanuil GeorgoulisMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will be able to demonstrate the basics from mathematical physics, including defining the many classical PDEs,derivation of some of them, and their properties. Moreover, they will be able to demonstrate the basic concepts and methodsfrom numerical analysis, such as writing a discretised scheme for a PDE, numerical approximation, eigenvalue problems, andconsistency, stability, and convergence analysis. Finally, students will be able to implement these numerical methods inMATLAB.

Teaching and Learning MethodsLectures, computer labs and problem classes.

Assessment MethodsThe coursework will consist of regularly assigned exercise sheets, including problem sets and computer assignments. Asubstantial amount of individual work will be required for a student to grasp the theoretical material (problem sets) and to getenough computational practice (computer exercises) to be able to solve PDEs numerically. The examination will have 5questions, and it will be possible to obtain a full mark by answering any 4 of them correctly.

Pre-Requisites

Co-RequisitesMA2021, MA2032 and MATLAB


Lectures 31Seminars

Practical Classes & Workshops 9Tutorials 10


Guided Independent StudyDemonstration





MA7011 Computational Methods for Partial Differential Equations




001 Coursework 30002 Exam (Final) 70 2003 Examination 100 2 Y

Period: Semester 1Occurence: ACoordinator: Ruslan DavidchackMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents should be able to utilise advanced methods of scientific computing in order to - Solve linear systems of equations- Solve nonlinear equations and systems of equations- Interpolate functions using polynomials and trigonometric functions (Fourier transform)- Calculate numerical approximations of derivatives and integrals of functions- Construct and analyse numerical methods for solving ordinary differential equations

Teaching and Learning MethodsLectures, problem classes, instructor-assisted computer lab sessions, revision problem sheets.

Assessment Methods1. Computer assignments designed to develop understanding of numerical algorithms and learn how to implement them in acomputer program (within Matlab). 2. Revision Problem Sheets for assessing students' understanding of theoretical material.3. Two hour examination.

Pre-RequisitesCalculus, Taylor's Thm, Linear Algebra

Co-RequisitesBasic programming, ordinary differential equations.


Lectures 20Seminars








MA7012 Scientific Computing




001 Exam (Final) 80 3002 Coursework 20003 Examination 100 3 Y

Period: Semester 2Occurence: ACoordinator: Simona PaoliMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents be able to discuss the assumptions made in using the generalized linear regression model and be able to calculateconfidence intervals and use hypothesis tests for model parameters. Also be able to assess the fit of a log-linear model usinga nested hierarchy of log-linear models. Students will demonstrate the theory of the generalized linear model and be able touse R to analyse data with the generalized linear model.

Teaching and Learning MethodsClass sessions with some handouts

Assessment MethodsMarked problem sheets, written examination

Pre-Requisites

Co-Requisites


Lectures 30Seminars








MA7021 Generalized Linear Models




002 Examination 50 2003 Problem Sheets 20004 Computational Tasks 30005 Examination 100 3 Y

Period: Semester 2Occurence: ACoordinator: Alexander GorbanMark Scheme: PGT Mark Scheme


Intended Learning OutcomesRepresent the structure of the data mining process and explain the basic notions and operation: data preprocessing, datacleaning, dimensionality reduction, binning, sampling, supervised and undervising learning, classification, clustering,regression, probability distribution estimation, entropy, information and information gain, independence and conditionalindependence, time series, stationary time series (in strong and weak sense).Analyse a data mining problem, recognise its type and select an adequate solution, from evaluation and cleaning of thedataset to slection of algorithms for data analysis. Analyse and validate results.Apply the basic methods and algorithms for data analysis, in particular: for classification kNN and decision tree algorithms, forclustering k-means, hierarchical clustering and density based algorithms, for prediction multivariate regression (linearregression and the kernel trick), for probability distribution estimation Bayes networks, for dimension reduction principlecomponent analysis, for time series use the basic models (white noise, random walk, moving average processes,autoregressive processes, integrated and ARIMA processes), apply mean filter and median filter, analyse trend and performsegmentation. Contruct basic neural networks for data analysis (Hopfield, Kohonen, cascade correlation and back-propagation of errors).

Teaching and Learning MethodsLectures, problem classes and computer practicals.

Assessment MethodsMarked fortnightly work, computer logs, written examination.

Pre-Requisites

Co-Requisites


Lectures 33Seminars 11

Practical Classes & Workshops 11Tutorials







MA7022 Data Mining and Neural Networks




001 Intermediate Test 20002 Examination (Final) 80 3003 Examination 100 3 Y

Period: Semester 1Occurence: ACoordinator: Nikolai BrilliantovMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe ability to define the classification of linear partial differential equations, and basic methods of its solution for one, two andthree dimensions. To apply the concepts of eigenfunctions, eigenvalues, and a Green function, to demonstrate an ability of itsapplication. To use the Fourier series and some special functions. To derive some basic equaltion of mathematical physics ofhyperbolic, parabolic and analyse the limits of its applications.

Teaching and Learning MethodsLectures, problem classes

Assessment MethodsThere will be an intermediate 1 hour test in the first half of the semester, based on the weekly problem sheets. A 3 hourexamination which will have 4 questions , with the full mark obtained by correctly answering 4 of them.

Pre-Requisites

Co-Requisites










MA7032 Equations of Mathematical Physics




002 Examination (Final) 90 3003 Coursework 10004 Examination 100 3 Y

Period: Semester 1Occurence: ACoordinator: Sergei PetrovskiyMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe student is required to demonstrate knowledge of the main principles of model building and analysis in population biologyand ecology.

Teaching and Learning MethodsLectures, seminars.

Assessment MethodsContinuous assessment is achieved through regular assessment of the student’s work at problem classes. Summativeassessment is also based on the results of written examination.

Pre-RequisitesCalculus and Differential Equations

Co-Requisites










MA7061 Topics in Mathematical Biology




001 Exam 100 3

Period: Semester 1Occurence: ACoordinator: Sergey UtevMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will obtain a thorough grounding in aspects of financial mathematics and derivative pricing. On completion of thismodule, a student will be able to confidently discuss the basic concepts and intruments of financial markets; be able to solveproblems in probability and stochastic processes; be able to use the knowledge of probability & stochastics to analysedifferent models of financial markets.

Teaching and Learning MethodsLectures, self study, and problem classes.

Assessment MethodsThe assessment of this module will consist of a 3 hour examination

Pre-Requisites

Co-Requisites










MA7071 Financial Mathematics I




001 Examination (Final) 100 3



Intended Learning OutcomesAfter finishing this module a student should be able to define the main concepts of financial market instruments. The studentshould be able the demonstrate the martingale technique and stochastic analysis to option pricing.

Teaching and Learning MethodsLectures, example classes, problem classes.

Assessment MethodsThe assessment of this module consists of a three hour examination.

Pre-RequisitesMA7071

Co-Requisites










MA7072 Financial Mathematics II





Period: Semester 2Occurence: ACoordinator: Andrey MudrovMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will have to investigate problems, make conjectures and draw conclusions. Students will demonstrate the use thetechniques taught within the module to solve problems, and be able to present arguments and solutions in a coherent, logical,and mathematically rigorous form.

Teaching and Learning MethodsLectures, courseworks, problem class sessions.

Assessment MethodsExam

Pre-RequisitesMA7071, elementary probability and statistics, real analysis and linear algebra, introductory financial mathematics

Co-RequisitesMA7072, MA7011










MA7073 Financial Risk




001 Exam (Final) 50 2002 Coursework 50003 Exam 100 2 Y

Period: Semester 1Occurence: ACoordinator: Ivan TyukinMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe students will be able to define, formulate, and classify linear and nonlinear optimization problems. With regards to linearoptimization (programming), they will explain the theory of the simplex method, and be able to use the method for solvingproblems with linear cost functions and constraints in the form of a convex polyhedron. In addition, the students will explaintechniques and methods for solving one-dimensional and multi-dimensional constrained and unconstrained nonlinearoptimization problems. The students will be able to solve shortest path and minimal-tree problems, and should know basicnotions and concepts from the theory of games. Application of programming skills to production of algorithms in VBA.

Teaching and Learning MethodsLectures, problem classes, computer practicals, automated computer assignments, VBA classes

Assessment MethodsClass tests, written reports on computer practicals, final exam, computer demonstration, Class computer test on linearprogramming and networks.

Pre-RequisitesLinear algebra, real analysis

Co-Requisites


Lectures 33Seminars








MA7077 Operations Research




001 Mini-projects 60002 Conference Presentation and Paper 40 3101 Examination 100 3 Y

Period: Semester 2Occurence: ACoordinator: Alexander GorbanMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe module will give an introduction to several particular classes of mathematical models, (physics, chemical kinetics,ecological dynamics, economical games, global dynamics).At the end of the module, a student should be able to:Explain the basic concepts and instruments of mathematical modellingDemonstrate simple models for real phenomenaExplain existing models of real phenomena when presentedExplain their model (methodology, results, criticisms) or critique of others through written and spoken means.

Teaching and Learning MethodsAn electronic textbook will be provided for self study and lectures.

Assessment MethodsMini- projects, assessed by 3,000 word report (60%)Internal conference presentation (20%) and Paper (20%)

Pre-Requisites

Co-Requisites










MA7080 Mathematical Modelling




001 Coursework 20002 Exam (Final) 80 2003 Examination 100 2 Y

Period: Semester 2Occurence: ACoordinator: Andrea CangianiMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThis module provides you with the mathematical foundation as well as implementation aspects of the numerical solution ofPartial Differential Equations (PDE), with focus on finite element methods. Within this module, students will have todemonstrate: - Ability to recognise the significance of the various terms and boundary conditions appearing in a partial differential equation(PDEs) models- the fundamental methods from numerical analysis, such as writing a discretised scheme for a PDE, numericalapproximation, consistency, stability, and convergenceanalysis. These concepts will be introduced using Finite Difference Methods and then applied to Finite Element Methods.- Knowledge of linear functional analysis and its relevance in PDE theory - Ability to deduce the right functional setting for a given PDE problem and to write its corresponding variational and finiteelement formulation - Knowledge of polynomial approximation theory- Knowledge of finite difference and finite elements error analysis- Understanding of the difference between a priori and a posteriori analysis - Basic knowledge of the practical relevance of adaptive techniques- Advanced knowledge of finite element coding techniques- Familiarity with freely available finite element libraries- Practical knowledge of finite difference and finite elements in more than one dimension gained thorough the implementationof common methods in MATLAB or freely available finite element libraries.

Teaching and Learning MethodsClass sessions/lectures, computer labs and problem classes.

Assessment MethodsThe coursework will consist of regularly assigned exercise sheets, including problemsets and computer assignments. A substantial individual work will be required for a student to grasp the theoretical material(problem sets) and to get enough computational practice (computer exercises) to be able to solve PDEs numerically. TheJune examination will have 4 questions based on the thought theory and some exercises. Full mark are obtained byanswering all 4 questions correctly.

Pre-RequisitesMatLab

Co-Requisites

Lectures 30Seminars








MA7091 Finite Element Theory and Applications




MA7091 Finite Element Theory and Applications





Period: Semester 2Occurence: A15Coordinator: Dalia ChakrabartyMark Scheme: PGT Mark Scheme


Intended Learning OutcomesPreparing the student with emplyability skills relevant to the data industry. The student will implement knowledge of appliedstatistics and data analysis skills, learnt as part of their DABI taught modules, to address a problem that arises in the realworld business context, in order to acheive objective business decisions. The student will learn to recall and analyse one ormore data sets in order to identify correlations amongst the different co-variates that can be modelled to bear influence uponthe observed system behaviour.

Teaching and Learning MethodsThe student will be guided by the project supervisor and present results/findings at the end of the semester. External industry-based supervisors, when relevant, will participate in the process of assessment of the project and its outcomes.

Assessment MethodsProject report and Presentation

Pre-Requisites

Co-Requisites


LecturesSeminars








MA7098 Data Analysis for Business Intelligence Project





Period: Semester 2Occurence: A15Coordinator: Andrea CangianiMark Scheme: PGT Mark Scheme


Intended Learning OutcomesConstruct, implement and complete an independent programme of research in a way that demonstrates an understanding ofthe concepts and methodologies appropriate to a modelling and scientific computing topic.Explain the purpose and significance of their research and place it in the context of existing literature and industry practice.The student will establish the lines of enquiry to be followed and produce a final thesis on this planned work. Students willproduce a written report on a substantial piece of work which will require the use of the library and other external resources.This will describe the methods learned, presenting arguments and solutions in a goherent and logical form.Students will give an oral and visual presentation to a group of peers, staff and industry contacts in a simulated conferenceenvironment. Students are required to submit a short paper summarising their work in advnace of the conference that is madeavailable to all participants.

Teaching and Learning MethodsLargely through independent study with directed activity initially led by the project supervisor. Students will be required torecord their weekly supervision meetings as well as attend department and university seminars.

Assessment MethodsFinal assessment will be froma combination of an oral presentation and paper (as part of the conference) and written thesis.

Pre-Requisites

Co-Requisites


LecturesSeminars


FieldworkProject Supervision 10






MA7099 ACNM Project




001 Exam (Final) 90 2002 Group poster presentation 10003 Exam 100 2 Y

Period: Semester 1Occurence: ACoordinator: Sibylle SchrollMark Scheme: PGT Mark Scheme


Intended Learning OutcomesDemonstrate the ability to construct and work with factor rings. Demonstrate the ability to prove and use tests for irreducibility. Demonstrate the ability to relate irreducible elements and maximal ideal in the ring of polynomials over a field. Demonstrate the ability to explain the significance and properties of the minimal polynomial.Demonstrate the ability to construct extension fields and use the concept of the degree of an extension. Demonstrate the ability to apply the concepts intorduced in the course may be appied to ruler and compass constructions. Demonstrate the ability to solve the three classical Greek questions discussed in this moduels.

Teaching and Learning MethodsLectures and problem classes.

Assessment MethodsExam, group project with poster presentation.

Pre-Requisites

Co-Requisites


Lectures 33Seminars








MA7101 Squaring the Circle and Irreducible Polynomials




001 EXAM (Final) 50 2002 Class Test 50003 Examination 100 2 Y

Period: Semester 2Occurence: ACoordinator: Jeremy LevesleyMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents should demonstrate the key concepts of this module; holomorphic functions, path integrals, Taylor and Laurentseries, singularities and residues of complex; functions. explain the main proofs given in the lectures and be able to determine whether a complex function is differentiable, define andevaluate path integrals, find Taylor and Laurent expansions of complex functions, calculate residues and use the residuetheorem to evaluate real integrals and sums of real series.

Teaching and Learning MethodsLectures and problem classes, coursework.

Assessment MethodsExam, class test

Pre-Requisites

Co-Requisites





Guided Independent Study 71Demonstration 3





MA7121 Complex Analysis




001 EXAM (Final) 90 2002 Project work 10

Period: Semester 1Occurence: ACoordinator: Alexander BaranovMark Scheme: PGT Mark Scheme


Intended Learning OutcomesTo define the concepts of symmetries, direct symmetries and isometries;To define the classification of finite groups of isometries in R2 and R3;To demonstrate the concepts of homomorphisms, normal subgroups and quotient groups and their relevance to the structureof a group;To explain the concept of a group action and to use group actions for enumeration and to prove fundamental results such asthe Sylow theorems;To calculate using generators and relations and to understand the idea of a group presentation in order to study a group;To define the properties of permutations and of symmetric and alternating groups;To explain the idea of simple groups as the basic building blocks of group theory;To explain and be able to use the main Sylow theorems for finite groups;To explain and be able to use the main Structure Theorem for finitely generated abelian groups.

Teaching and Learning MethodsLectures and problem classes

Assessment MethodsExam and problem sheets

Pre-Requisites

Co-Requisites










MA7131 Groups and Symmetry




001 Examination 90 2002 Group Project 10003 Examination 100 2 Y

Period: Semester 2Occurence: ACoordinator: Alexander ClarkMark Scheme: PGT Mark Scheme


Intended Learning OutcomesIn this module, students will learn core material in homotopy theory, identifying and distinguishing global topologicalphenomena in a variety of mathematical systems, and will define some of the classical tools for analysing and utilising suchinformation. In the guided groups, students will select, work through in detail, and present examples of important current orclassical applications of homotopy theory in a variety of possible areas of mathematics and related disciplines, such asgeometry, algebra, dynamics, data analysis, economics and biology.

Teaching and Learning MethodsLectures with unassessed problem sheets and assignments; problem or revision classes; guided group work on projects.

Assessment MethodsExamination and group project work assessed by presentaion and written report.

Pre-Requisites

Co-Requisites



Practical Classes & WorkshopsTutorials 12

FieldworkProject Supervision 2






MA7144 Topology and its Applications




001 Skills Test 40002 Class Test 30003 Project 30004 Exam 100 2 Y

Period: Semester 2Occurence: ACoordinator: Katrin LeschkeMark Scheme: PGT Mark Scheme


Intended Learning OutcomesTo define the definitions and the key concepts of curves and surfaces. To be able to reproduce and apply the main results and proofs given in the module. To demonstrate familiarity with the topic and to be able to solve routine problems. To define how to connect visual information with geometric properties.To be able to produce mathematical exhibits and to communicate mathematical content to non-experts.

Teaching and Learning MethodsLectures, example classes, example sheets, group project

Assessment MethodsComputer tests, class test and group project

Pre-Requisites

Co-Requisites


Lectures 33Seminars








MA7152 Curves and Surfaces




001 EXAM (Final) 90 2002 Group work 10003 Exam 100 2 Y

Period: Semester 2Occurence: ACoordinator: Frank NeumannMark Scheme: PGT Mark Scheme


Intended Learning OutcomesTo define the definitions and the key concepts of elementary number theory and to be able to reproduce and apply the mainresults and proofs given in the module. To demonstrate how to formulate number theoretical problems in rigorousmathematical language. To demonstrate familiarity with the topic and to be able to solve routine problems.

Teaching and Learning MethodsLectures, example classes, example sheets

Assessment MethodsMarked problem sheets, written examination

Pre-Requisites

Co-Requisites


Lectures 33Seminars








MA7153 Number Theory




001 Coursework 50002 Project work 50101 Exam 100 2 Y

Period: Semester 1Occurence: ACoordinator: Katrin LeschkeMark Scheme: PGT Mark Scheme


Intended Learning OutcomesAt the end of this modules, a student should be able to demonstrate the defiinitions, key concepts and proofs of minimalsurfaces, in particular, the notions of mean curvature, conformal parametrisation, Weierstrass Data, Weierstrassrepresentation, associated family, Lopez-Ros deformation.Students should be able to discover the associated family and the Lopez-Ros deformation of standard minimal surfaces andvisualise them. Students will be able to apply the concepts of the lecutuers to new minimal surfaces and present the resultsin a written report.

Teaching and Learning MethodsLectures, example classes, project work, oral presentations. Independent study.

Assessment MethodsCourse work exercises and written project.

Pre-Requisites-

Co-Requisites-


Lectures 10Seminars








MA7155 Minimal Surfaces




001 Exam (Final) 70 2002 Project 30

Period: Semester 1Occurence: ACoordinator: Stephen GarrettMark Scheme: PGT Mark Scheme


Intended Learning OutcomesOn completion of this module, students will be able to demonstrate cashflow models to financial and business scenarios, andbe able to define standard actuarial notation and fundamental financial concepts. The student will be able to define the role ofactuaries in the financial sector.

The student will also practice the ability to self study - an important skill for lifelong learning in any chosen profession.

Full syllabus CT1: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsStudents will be provided with material written specifically for self study which will be paced across the semester.One lecture will be given per week and the onus is on self study. This study will be supported via electronic means onblackboard. One example class per week will be given to go through regular (non-assessed) coursework.

Assessment MethodsThe assessment for this module will consist of a 2hr examination on unseen questions and a substantial independentresearch project/case-study report. This is an individual, open-ended task which requires the student to demonstrate self-direction and originality in tackling and solving problems, and act autonomously in planning and implementing tasks at aprofessional level. It is also intended to develop the student's transferable skills in line with QAA descriptors.

Pre-Requisites

Co-Requisites










MA7401 Theory of Interest




001 Exam 70 2002 Coursework 30

Period: Semester 2Occurence: ACoordinator: Leena SodhaMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThe module aims to give actuarial students a solid grounding in finance and accounting. Students will define the fundamentalframework of UK finance and be able to write/interpret company accounts. Tax and the international perspective are alsoconsidered.Full syllabus CT2: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsIntensive lecture sessions, self study, VLE.


Pre-Requisites

Co-Requisites










MA7402 Finance and Financial Reporting





Period: Semester 1Occurence: ACoordinator: Bogdan GrechukMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will define and apply the concepts of statistical inference.

Full syllabus CT3: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsLectures and self study

Assessment Methods2 hour written examination intended to assess technical skills.Substantial independent research project/case study report. This is an individual open ended task which requires the studentto demonstrate self direction and originality in tackling and solving problems and act autonomously in planning andimplementing tasks at a professional level. It is also intended to develop the student's transferable skills in line with QAAdescriptors.

Pre-Requisites

Co-Requisites


Lectures 33Seminars








MA7403 Statistics





Period: Semester 1Occurence: ACoordinator: Bogdan GrechukMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will be introduced to the need and theory of modelling within the financial world. Part of the CT4 Syllabus is coveredin this module with the remainder covered under MA7414.Full syllabus CT4: http://www.actuaries.org.uk/students/pages/syllabus-examsStudents will be able to:Discuss the principles of actuarial modellingDiscuss the general principles of stochastic processes and their classification info different typesDefine and apply a Markov chainDefine and apply a Markov process

Teaching and Learning MethodsStudents will be provided with material written specifically for the module. Three lectures per week will be used to teach thedetails of the material. Students are further supported with 1 problem class per week.

Assessment Methods2 hour written exam. Substantial independent research project/case-study report which is an individual open-ended taskwhich requires the student to demonstrate self-direction and originality in tackling and solving problems, and actautonomously in planning an implementing tasks at a professional level.

Pre-Requisites

Co-Requisites






Supervised time in studio/workshopWork Based Learning 69




MA7404 Models





Period: Semester 2Occurence: ACoordinator: Bo WangMark Scheme: PGT Mark Scheme


Intended Learning OutcomesDefine standard actuarial notation and fundamental life contracts; Use mathematical methods to describe and model various life contracts; Calculate the associated quantities in varios life contracts;Value cashflows dependent on death, survival or other uncertain risksDiscuss factors affecting mortality and morbidity rates.Full syllabus CT5: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsLectures, problem classes, self study

Assessment Methods3 hour written examination intended to assess technical skills.Substantial independent research project/case study report. This is an individual open ended task which requires the studentto demonstrate self direction and originality in tackling and solving problems and act autonomously in planning andimplementing tasks at a professional level. It is also intended to develop the students transferrable skills in line with QAAdescriptors.

Pre-RequisitesMA7401, MA7403, MA7414

Co-Requisites


Lectures 30Seminars








MA7405 Contingencies




001 Exam (Final) 70 2002 Coursework 30

Period: Semester 2Occurence: ACoordinator: Nick FosterMark Scheme: PGT Mark Scheme


Intended Learning OutcomesExplain the idea of Bayesian statistics and calculate the posterior distribution and Bayesian estimation.Discuss the credibility approach and demonstrate how Bayesian statistics are applied in credibility theory.Motivate the use of GLM in a financial context. Reproduce underlying mathematics and apply in standard situations.Motivate the use of time series methods; reproduce underlying mathematics and apply in standard situationsMotivate the ise of Monte Carlo simulations; reprodude underlying mathematics and apply in existing simulations.Full syllabus CT6: http://www.actuaries.org.uk/students/pages/syllabus-exams(CT6 (v), (vii), (viii), (ix))

Teaching and Learning MethodsStudents will be provided with material written specifically for this module. Two lectures per week will be delivered. Studentswill be further supported with one problem class per week. An individual open ended case study that requires the student to demonstrate self direction and originality in tackling andsolving problems will be set.

Assessment Methods2 hour written examination intended to assess technical skills.Substantial independent research project/case study report. This is an individual open ended task which requires the studentto demonstrate self direction and originality in tackling and solving problems and to act autonomously in planning andimplementing tasks at a professional level. It is also intended to develop the students transferrable skills in line with QAAdescriptors.

Pre-RequisitesMA7403

Co-RequisitesTogether with MA7416 this module covers CT6 syllabus


Lectures 20Seminars








MA7406 Further Statistics





Period: Semester 2Occurence: A15Coordinator:Mark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will learn the fundamentals of economics within a business context. The learning style is intended to preparestudents for future independent study.See the full syllabus: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsThe teaching method will mirror the DL programme. Predominantly self study with some tutorials.

Assessment Methods3 hour exam

Pre-Requisites

Co-Requisites


LecturesSeminars 10








MA7407 Business Economics




001 Exam (Final) 70 3002 Coursework 30



Intended Learning OutcomesStudents will define and demonstrate aspects of financial mathematics and derivative pricing. Along side MA7418 this modulecovers a half of CT8 syllabus.Full syllabus CT8: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsLectures, self study and problem classess.

Assessment MethodsThe final assessment of this module will consist of a 3 hour exam.Substantial independent research project/case-study report. This is an individual, open-ended task which requires the studentto demonstrate self-direction and originality in tackling and solving problems, and act autonomously in planning andimplementing tasks at a professional level. It is also intended to develop the student's transferable skills in line with QAAdescriptors

Pre-Requisites

Co-Requisites










MA7408 Financial Mathematics




001 Project 50002 Presentation 50

Period: Semester 2Occurence: A15Coordinator: Leena SodhaMark Scheme: PGT Mark Scheme


Intended Learning OutcomesThis critical-thinking and business-awareness module is intended to satisfy both QAA descriptions and market needs. Themodule is run jointly by the department and external specialists. The module is practical and covers:• Industry developments and challenges – an overview covering all actuarial practice areas • Strategic thinking – extended case studies and problem solving techniques • Business games – team working, innovative thinking and problem solving.• Professionalism and ethics – principles and case studies • Personal development – an overview of lifelong learning and work based skills • Legal principles• Presentation skills

Teaching and Learning MethodsThe module is delivered via a short residential school (held on campus). It is assessed by presentations and a 5,000 worddissertation. The dissertation will require students to apply technical skills and business awareness/critical thinking to a real-world problem presented as a case study. The students will be assessed on technical expertise, innovative thinking and abilityto independently research and understand an unfamiliar business scenario.

Assessment MethodsDissertation, presentations, completion of residential school.

Pre-Requisites

Co-Requisites

Excluded CombinationsCannnot be taken with MA7006 The MSc Actuarial Sciences Project









MA7409 Business Awareness and Critical Thinking




001 Exam (Final) 70 2002 Mini-Project 30

Period: Semester 2Occurence: ACoordinator: Stephen GarrettMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will develop the necessary skills to contruct asset liability models and to value financial derivatives.

By the end of the course a student should be able to: • Apply income valuation methodologies to financial and business scenarios.• Understand the action of compound interest.• Understand fundamental financial concepts and standard actuarial notation..• Have a good understanding of the significance of actuarial involvement in the financial sector.• Be capable of passing the Institute & Faculty of Actuaries' CT1 examination.

Full syllabusCT1: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsStudents will be provided with Distance Learning self study material in the form of a Wiki. To support students, access will beprovided to a tutor throughout the Semester and a series of revision lectures will also be provided at the end of the Semester.

Assessment MethodsThe assessment for this module will consist of a 2 hour exam on unseen questions, a 3,000 work mini-project in response toan open ended problem, and formative assessment is due throughout the module as regular problem sheets.

Pre-Requisites

Co-Requisites


Lectures 5Seminars








MA7410 Income Valuation





Period: Semester 1Occurence: ACoordinator: Andrey MorozovMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will be introduced to the fundamental notation and processes in studying human mortality data in an actuarialcontext.

The student will also practice the ability to self study - an important skill for lifelong learning in any chosen profession.

Full syllabus CT4 from (v): http://www.actuaries.org.uk/students/pages/syllabus-exams.

Teaching and Learning MethodsStudents will be provided with material written specifically for self study which will be paced across the semester. One lecturewill be given per week and the onus is on self study. This study will be supported via electronic means on blackboard. Oneexamples class per week will be given to go through regular (non-assessed) coursework.


Pre-Requisites

Co-Requisites










MA7414 Mortality




001 Exam 70 2002 Project 30

Period: Semester 2Occurence: ACoordinator: Dalia ChakrabartyMark Scheme: PGT Mark Scheme


Intended Learning OutcomesStudents will learn further statistical methods relevant to the actuarial industry.Part of the CT6 Syllabus is covered in this module with the remainder covered under MA7406.Full syllabus CT6: http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsLectures, self study.

Assessment Methods2 hour written exam. Substantial independent research project/case-study report.

Pre-RequisitesMA7403, MA7406

Co-Requisites










MA7416 Applied Statistics




001 Exam 70 2002 Project/case study 30

Period: Semester 2Occurence: ACoordinator: Aihua ZhangMark Scheme: PGT Mark Scheme


Intended Learning OutcomesOn completion of this module students will be able to:Describe and discuss the application of utility theory to economic and financial problems.Discuss the advantages and disadvantages of different measures of investment risk.Describe and discuss the assumptions of mean-variance portfolio theory and its principal results.Describe and discuss the properties of single and multifactor models of asset returns.Describe asset pricing models, discussing the principal results and assumptions and limitations of such models.Discuss the various forms of the Efficient Markets Hypothesis and discuss the evidence for and against the hypothesis.Demonstrate a knowledge and understanding of stochastic models of the behaviour of security prices.Demonstrate a knowledge and understanding of models of the term structure of interest rates.These map to components (i)- (vii) and (x) of the latest CT8 syllabus. The full CT8 syllabus can be found from the link http://www.actuaries.org.uk/students/pages/syllabus-exams

Teaching and Learning MethodsStudents will be provided with material specifically written for the module. Three lectures per week (shared with UG studentson MA3418) will be used to teach the details of the material. Students are further supported with 1 problem class (shared). Anindividual open ended case study that requires the student to demonstrate self-direction in tackling and solving problems willbe set.

Assessment Methods3 hour written exam intended to assess technical skills.Substantial independent research project/case-study report.’ Should be changed to 2 hour written exam intended to assess technical skills.Substantial independent research project/case-study report.

Pre-Requisites

Co-Requisites










MA7418 Financial Engineering




001 Attendance 100

Period: Semester 1Occurence: ACoordinator:Mark Scheme: PGT Attendance Only


Intended Learning OutcomesThroughout this course, the students will be able to demonstrate the basic background knowledge of SAS and be able toprepare for the SAS Base Certification Exam. To pass the exam, students should be able to:• Import and export raw data files• Manipulate and transform data• Combine SAS data sets• Create basic detail and summary reports using SAS procedures• Identify and correct data, syntax and programming logic errors

Teaching and Learning MethodsComputer classes

Assessment MethodsAttendance only

Pre-Requisites

Co-Requisites


LecturesSeminars








MA7901 SAS Training




001 Attendance Only 100

Period: Semester 1Occurence: ACoordinator: Alexander BaranovMark Scheme: PGT Attendance Only


Intended Learning OutcomesStudents will be able to demonstrate programming ability in VBA. Supporting master programmes.

Teaching and Learning MethodsLectures and computer classes

Assessment MethodsAttendance Only

Pre-Requisites

Co-Requisites


Lectures 3Seminars








MA7902 VBA Training




001 Attendance 100

Period: Academic YearOccurence: ACoordinator:Mark Scheme: PGT Attendance Only


Intended Learning OutcomesAll students in the Department are divided into four Houses: Noether House, Gauss House, Newton House, Euler HouseA House is a community of staff and students which provides a support structure for the academic and social aspects of thestudents’ University life. It helps students develop strong ties and friendships with fellow students, gives them a sense ofbelonging and opportunities to develop their leadership, mentoring, and teamwork skills.Some of the goals of the House System include:• To create a structure and timetabled activities of the student body, which will help the associated staff members to becomemore familiar with the students in their Houses, fostering a more personal connection between staff and students;• To give the students a sense of belonging;• To create rituals to mark important events in the lives of the students;• To organise the lives of the students by providing a framework for work and social activities;• To provide a natural setting for competition among students, both mathematical and athletic;• To organise the teaching of small groups to mesh with the House System;• To provide a framework for peer support and mentoring of junior students by senior students;• To provide students with a forum for presentations and public speaking.The associated staff members of the House include the House Tutor and Personal Tutors. Students will maintain theirassociation with the House throughout their studies at Leicester. Each House will have a site on Blackboard(blackboard.le.ac.uk) and all the information on the structure of student support, announcements, activities, discussionboards, and chats on House-related subjects can be found there.The life of a House is organised around regular meetings of associated staff and students during the House Hour.

Teaching and Learning Methods


Pre-Requisites

Co-Requisites


LecturesSeminars 44








MA7903 House Hour




001 Attendance 100

Period: Semester 2Occurence: ACoordinator:Mark Scheme: PGT Attendance Only


Intended Learning OutcomesIt is intended that students achieve understanding of the underlying concept of SQL and learn the computational applicationsof SQL towards achievement of communication with databases, including querying and managing databases andimplementing data warehouses. Students will be prepared for the external assessments leading to a Microsoft certification inSQL.

Teaching and Learning MethodsComputer classes


Pre-Requisites

Co-Requisites


LecturesSeminars








MA7904 SQL Training


module specification - university of leicesterapply the basic methods and algorithms for data...

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