course guide bsc (hons) artificial intelligence and robotics

School of Mathematics and Computer ScienceBSc (Hons) Artificial Intelligence and Roboticswith Sandwich PlacementCourse Guide

2018-19September

About this guide

This is your course guide. It provides the basic but fundamental information about your course of study. Thisguide is yours for the duration of the course, we don’t re-issue it annually and if any information containedwithin were to change then we will write to you to explain so.

In particular, if any important aspects relating to your modules were to change then we will inform you inaccordance with the Code of Practice for the Management of Changes to Modules and Courses. The teachingand support teams which you will get to know over time will refer to this guide – it will be useful to you andwe advise you to make good use of it throughout your studies.

The Course Guide should be read in conjunction with the more general sources of information which relate toall students at the University. The Student Handbook is a very detailed reference point for all issues relating toyour studies which aren’t specific to just your particular course. You might also want to refer to the StudentCharter; the University’s Policies and Regulations and the University Assessment Handbook documents whichwill provide you with all of the information that we think you will need for your period of study here.

If you need additional information, or you simply want to discuss elements of any of these documents or otheraspects of your course, find that there is something you need to know, please contact your Faculty StudentServices:

Faculty Student Services

We can help with the administration and organisation of your time at University – from enrolment andmodule registration, tuition fee enquiries, attendance support, course management and lifecycle queries,extenuating circumstances, leave of absence, transfers and changes, assignment submission, SAMsappointments, assessment and result queries, right through to Graduation.

You can also come and talk to us for impartial advice and support if things are starting to go wrong and you’renot sure who else to talk to. The main thing to remember is that you are not alone. We see large numbers ofstudents over the course of a year on a variety of issues, so please don’t be afraid to approach us.

We are here to ensure that your transition into Higher Education is as smooth as possible. Normal officeopening hours are Monday-Friday 08:45-17:00.

You can contact us through the e:vision help desk, by phone or in person or by e-mail:

Faculty of Science andEngineering (CityCampus)

Alan Turing Building MI 024 (01902) 322129 [email protected]

Faculty of Science andEngineering (TelfordCampus)

The Darby Building SC 041 (01902) 322129 [email protected]

Help and Advice is alsoavailable from StudentSupport & Wellbeing…

Contact us at the Alan TuringBuilding MI 001 for all enquiries andreferrals… Services operate at allcampuses by appointment.

(01902) 321074(01902) 321070

[email protected]@wlv.ac.uk

Welcome from the Course Leader

On behalf of the teaching and support teams from BSc (Hons) Artificial Intelligence and Robotics withSandwich Placement course, I would like to extend to you a very warm welcome to the University ofWolverhampton, and in particular your campus.

My name is Dr Sarah Slater and I am the course leader for your BSc (Hons) Artificial Intelligence and Robotics

with Sandwich Placement course and alongside your personal tutor, will be your main point of contact overthe duration of your studies. My contact details are below – please don’t hesitate to get in touch if you needany support or guidance.

The successes which you will achieve whilst at the University are based upon a partnership between theexpertise and support from the staff here and the effort you put into learning. We welcome students who areeager to think for themselves, to take control of their own learning and who are ready to get involved indeveloping the skills required in a highly competitive job market. Make the most of the wide range ofopportunities available to you.

Studying at University can be difficult, and for many of you the transition into University life will bechallenging. However we will support you throughout your course, particularly whilst you develop into anindependent learner over the course of your first year with us.

We believe it is important that you are encouraged to make your own contribution to the effective operationand development of your chosen course. We hope that you might consider acting as a Course Representativeduring some of your time with us to help the University continue to improve your experience.

I would like to wish you every success with your studies. We look forward to working with you and hope thatyou enjoy your time with us.

Sarah

on behalf of the team

Course Management and Staff Involvement

RoleRole NameName SpecialismSpecialism eMaileMail Tel. Ext.Tel. Ext. RoomRoom

Head of School Professor Amar Aggoun [email protected] 1487 MI114

Course Leader Dr Sarah Slater [email protected] 1492 MI219

Head of Department Dr Kevan Buckley [email protected] 1836 MI123

Faculty Enabling Tutor Matthew Howell [email protected] 1448 MI138

Student Advisor Miss Kimberley Turner [email protected] 3577 MI024

Educational Aims of the Course

The robotics and artificial intelligence (AI) fuelled by the rise in computer processing power, the profusion ofdata, and the development of techniques such a ‘deep learning’ is undergoing a major transformation. AI-enabled Robots are growing beyond being the workhorses of industrial shop floors, and beginning to assumethe roles of personal assistants, delivery vehicles, surgical assistants, assist doctors with medical diagnoses,exoskeletons, driverless vehicles, and unmanned aerial vehicles (UAVs), among many others.

Given that Robotics and Artificial Intelligence have an important degree of interdependency, this course bringstogether these two areas, and offers conceptual grounding in intelligent systems, and the chance to applytheoretical knowledge in a practical setting.

An artificial intelligence and robotics degree will provide graduates with a fantastic platform from which toenter a wide range of challenging sectors: such as Finance, Engineering, IT & Technology, Manufacturing &Production, Transport & Logistics, Public Sector, Defense, Healthcare, Entertainment and Science.

What makes this programme distinctive?

The course is taught by experienced academics, who are deeply involved in research and have experience ofcollaborating with industry experts. These academics are also able to transfer their knowledge and skills tothe students. The course also provides the opportunity for students to work with industry on some modulesso that theoretical underpinning is enhanced with real-life experience.

A placement can be undertaken anywhere; local or national for example. During a placement, you will be doingsimilar work to a normal employee of the organisation giving you a unique insight into your chosenprofession or sector, the opportunity to acquire crucial personal skills and also the opportunity to build anetwork of useful contacts.

The team at The Workplace constantly search for new placement opportunities but if you find an opportunitythat interests you or you have been successful in securing one yourself, contact them for further informationand support.

Students choosing to undertake a placement will gain (Sandwich) on their degree classification.

Course Structure

September (Full-Time)September (Full-Time)

Year 1Year 1

Full time and Sandwich Undergraduate Honours students normally study 120 credits per academic year; 60credits semester 1 and 60 credits semester 2.

ModuleModule TitleTitle CreditsCredits PeriodPeriod TypeType

4CI018 Academic Skills and Team-based Learning 20 SEM1 Core

4CS001 Introductory Programming And Problem Solving 20 SEM1 Core

4CS015 Fundamentals of Computing 20 SEM1 Core

4CS017 Internet Software Architecture 20 SEM2 Core

4MM013 Computational Mathematics 20 SEM2 Core

4CS016 Embedded Systems Programming 20 SEM2 Core


Year 2Year 2



5CS019 Object-Oriented Design and Programming 20 SEM1 Core

5CS036 Robotic Engineering 20 SEM1 Core

5CS037 Concepts and Technologies of AI 20 SEM1 Core

5CS029 Sensors Actuators and Smart Environments 20 SEM2 Core

5CS028 Embedded Programming and Smart Systems 20 SEM2 Core

5CS0245CS016 Professional Experience and Development 20 SEM2 Core

https://www.wlv.ac.uk/current-students/careers-enterprise-and-the-workplace/the-workplace/student-support/placements-/


Year 3Year 3



5MM006 Industrial Placement 40 YEAR Core


Year 4Year 4



6CS026 Systems Architecture and Internet of Things 20 SEM1 Core

6CS005 High Performance Computing 20 SEM1 Core

6CS012 Artificial Intelligence and Machine Learning 20 SEM2 Core

6CS036 Project and Professionalism with AI and Robotics Artefact 40 YEAR Core

6CS033 AI and mobile robots 0 SEM2 Core

Course Learning Outcomes

Learning OutcomeLearning Outcome Contributing ModulesContributing Modules

CertHE Course Learning Outcome 1 CertHE Course Learning Outcome 1 (CHECLO1)(CHECLO1)

Demonstrate knowledge of the underlyingconcepts and principles associated with yourarea(s) of study, and an ability to evaluate andinterpret these within the context of that area ofstudy.

4CI018 Academic Skills and Team-based Learning4CS001 Introductory Programming And Problem Solving4CS014 Team-based Learning Project4CS015 Fundamentals of Computing4CS016 Embedded Systems Programming4CS017 Internet Software Architecture4MM013 Computational Mathematics


Demonstrate an ability to present, evaluate andinterpret qualitative and quantitative data, inorder to develop lines of argument and makesound judgements in accordance with basictheories and concepts of your subject(s) of study.

4CI018 Academic Skills and Team-based Learning4CS001 Introductory Programming And Problem Solving4CS014 Team-based Learning Project4CS015 Fundamentals of Computing4CS017 Internet Software Architecture4MM013 Computational Mathematics


Evaluate the appropriateness of differentapproaches to solving problems related to yourarea(s) of study and/or work.

4CI018 Academic Skills and Team-based Learning4CS001 Introductory Programming And Problem Solving4CS014 Team-based Learning Project4CS015 Fundamentals of Computing4CS017 Internet Software Architecture4MM013 Computational Mathematics


Communicate the results of your study/work

4CI018 Academic Skills and Team-based Learning4CS014 Team-based Learning Project

accurately and reliably, and with structured andcoherent arguments.

4CS015 Fundamentals of Computing4CS016 Embedded Systems Programming4CS017 Internet Software Architecture4MM013 Computational Mathematics


Demonstrate the qualities and transferable skillsnecessary for employment requiring the exerciseof some personal responsibility.

4CI018 Academic Skills and Team-based Learning4CS001 Introductory Programming And Problem Solving4CS014 Team-based Learning Project4CS015 Fundamentals of Computing4CS016 Embedded Systems Programming4CS017 Internet Software Architecture

DipHE Course Learning Outcome 1 DipHE Course Learning Outcome 1 (DHECLO1)(DHECLO1)

Demonstrate knowledge and criticalunderstanding of the well-established principlesof your area(s) of study, and of the way in whichthose principles have developed with anunderstanding of the limits of your knowledge,and how this influences analyses andinterpretations based on that knowledge.

5CS016 Professional Experience and Development5CS019 Object-Oriented Design and Programming5CS024 Collaborative Development5CS028 Embedded Programming and Smart Systems5CS029 Sensors Actuators and Smart Environments5CS036 Robotic Engineering5CS037 Concepts and Technologies of AI


Demonstrate knowledge of the main methods ofenquiry in the subject(s) relevant to the namedaward, and ability to evaluate critically theappropriateness of different approaches tosolving problems in the field of study.

5CS016 Professional Experience and Development5CS019 Object-Oriented Design and Programming5CS024 Collaborative Development5CS028 Embedded Programming and Smart Systems5CS029 Sensors Actuators and Smart Environments5CS036 Robotic Engineering5CS037 Concepts and Technologies of AI


Use a range of established techniques to initiateand undertake critical analysis of information,and to propose solutions to problems arising fromthat analysis.

5CS019 Object-Oriented Design and Programming5CS028 Embedded Programming and Smart Systems5CS029 Sensors Actuators and Smart Environments5CS036 Robotic Engineering5CS037 Concepts and Technologies of AI


Effectively communicate information, argumentsand analysis in a variety of forms to specialist andnon-specialist audiences, and deploy keytechniques of the discipline effectively.

5CS016 Professional Experience and Development5CS024 Collaborative Development5MM006 Industrial Placement


Demonstrate the qualities and transferable skillsnecessary for employment, requiring the exerciseof personal responsibility and decision-makingand undertake further training, developingexisting skills and acquire new competences thatwill enable them to assume significantresponsibility within organisations.

5CS016 Professional Experience and Development5CS019 Object-Oriented Design and Programming5CS024 Collaborative Development5CS028 Embedded Programming and Smart Systems5CS029 Sensors Actuators and Smart Environments5CS036 Robotic Engineering5CS037 Concepts and Technologies of AI5MM006 Industrial Placement

Ordinary Course Learning Outcome 1Ordinary Course Learning Outcome 1(ORDCLO1)(ORDCLO1)

Apply a full understanding, knowledge andexperience of the principles of AI to design andbuild robots to perform specific tasks and reflectupon the efficiency and functionality of theirperformance.

6CS012 Artificial Intelligence and Machine Learning6CS033 AI and mobile robots


Demonstrate the ability to apply underlyingconcepts and principles outside the context inwhich they were first studied, including, whereappropriate, the application of those principles inan employment context.

5CS016 Professional Experience and Development5CS019 Object-Oriented Design and Programming5CS024 Collaborative Development5CS028 Embedded Programming and Smart Systems5CS029 Sensors Actuators and Smart Environments5CS036 Robotic Engineering

5CS037 Concepts and Technologies of AIOrdinary Course Learning Outcome 2Ordinary Course Learning Outcome 2(ORDCLO2)(ORDCLO2)

Demonstrate and apply knowledge of computerhardware and software with particular referenceto the application of computing practice to thedesign and realisation of mobile robots.

6CS033 AI and mobile robots


Apply appropriate theory, tools and techniques(e.g. theory and practice of programming, object-oriented design and analysis, AI technologies) tothe analysis, design and synthesis of solutions torequirements in the domain of Computer Science.

6CS005 High Performance Computing6CS012 Artificial Intelligence and Machine Learning6CS026 Systems Architecture and Internet of Things6CS033 AI and mobile robots


Demonstrate mastery of the essential facts,concepts, principles, theories and practicesenabling graduate employment in applications ofComputer Science (e.g. Software development,media computing, systems analysis).

6CS005 High Performance Computing6CS012 Artificial Intelligence and Machine Learning6CS026 Systems Architecture and Internet of Things6CS033 AI and mobile robots


Demonstrate a range of social, legal, ethical,professional and project management skillsrequired for continuing professional developmentin the domain of AI and Robotics within a world-wide context.

6CS033 AI and mobile robots

Honours Course Learning Outcome 1Honours Course Learning Outcome 1(DEGCLO1)(DEGCLO1)

Apply a full understanding, knowledge andexperience of the principles of AI to design andbuild robots to perform specific tasks and reflectupon the efficiency and functionality of theirperformance.

6CS012 Artificial Intelligence and Machine Learning6CS033 AI and mobile robots6CS036 Project and Professionalism with AI and Robotics Artefact


Demonstrate and apply knowledge of computerhardware and software with particular referenceto the application of computing practice to thedesign and realisation of mobile robots.

6CS033 AI and mobile robots6CS036 Project and Professionalism with AI and Robotics Artefact


Apply appropriate theory, tools and techniques(e.g. theory and practice of programming, object-oriented design and analysis, AI technologies) tothe analysis, design and synthesis of solutions torequirements in the domain of Computer Science.

6CS005 High Performance Computing6CS012 Artificial Intelligence and Machine Learning6CS026 Systems Architecture and Internet of Things6CS033 AI and mobile robots6CS036 Project and Professionalism with AI and Robotics Artefact


Demonstrate mastery of the essential facts,concepts, principles, theories and practicesenabling graduate employment in applications ofComputer Science (e.g. Software development,media computing, systems analysis).

6CS005 High Performance Computing6CS012 Artificial Intelligence and Machine Learning6CS026 Systems Architecture and Internet of Things6CS033 AI and mobile robots6CS036 Project and Professionalism with AI and Robotics Artefact


Demonstrate a range of social, legal, ethical,professional and project management skillsrequired for continuing professional developmentin the domain of AI and Robotics within a world-wide context.

6CS033 AI and mobile robots6CS036 Project and Professionalism with AI and Robotics Artefact


Demonstrate the ability to gather, evaluate andreflect on information from relevant sources andsolutions to problems in the domain of AI andRobotics.

6CS036 Project and Professionalism with AI and Robotics Artefact

PSRB

None

Employability in the Curriculum

As AI and Robotics technologies develop, they are going to create a demand for new skills. The graduates willdevelop a portfolio during their course which will give them suitable experience in order to present toemployers of practical skills required from industry. Students will also be encouraged to pursue a project withan industry partner, giving them ‘industry experience’. The students will also be encouraged to take part innational and international competitions which will further how involvement with external stakeholders.

The transferrable skills such as problem identification, analysis, modelling, solution developing andevaluation gained in this course will prepare the students for a range of careers. The modules related to thisaward will be conscious of conformance to the University Employability + enterprise award, to ensure thatrelevant support and guidance is embedded in the curriculum.

The most common fields where employment can be found will be in industries developing robotic solutionsfor manufacturing, healthcare, transport, energy, defence, research, etc. Graduates roles could include,

Robotics Design specialistSoftware engineer/developerEmbedded Systems developerIntelligent Systems architectIntelligence analyst in a range of sectors such as Finance

Further study (Computer Science Masters courses, PhDs researching)

Teaching, Learning and Assessment

The learning activities on your course will develop distinctive graduate attributes that will make you stand outand enhance your employability. These skills will be embedded into the curriculum throughout your course.Examples include:

Digitally Literacy: All Computer Science graduates will surely be users of advanced technologies. However, onyour course you will develop your skills to encompass literacy more fully such as learning how to findinformation and how to take best advantage of digital resources and the Internet to make you effective in theInformation Age.

Global Citizenship: On each level of your course you will learn about social, legal and ethical aspects ofComputing, which will broaden your understanding of the way the world works and how communication andcollaboration are evolving.

Knowledgeable and Enterprising: Throughout your course you will build up your professional andemployability skills and learn to apply the knowledge you have acquired in an enterprising way. You willconstantly nurture your own intellectual curiosity. The tools, methodologies and techniques that you willlearn have been carefully selected to prepare you with the skills that employers demand and the opportunitiesfor work based learning and placements will allow you to gain the vital experience that they often expect.

Reference Points

Quality Code - Part A: Setting and Maintaining Academic Standards. Including :

Qualifications Frameworks

Characteristics Statements

Credit Frameworks

Subject Benchmark Statements

Quality Code - Part B: Assuring and Enhancing Academic Quality

University Policies and Regulations

Equality Act (2010)

QAA Subject Benchmark for Computing

HEA Employability Profiles for Computing

Skills Framework for the Information Age

e-Skills

British Computer Society

Academic Regulations Exemptions

None

Support with your studies

University Learning Centres are the key source of academic information for students providing access to:

Physical library resources (books, journal, DVDs etc.)Study areas to allow students to study in the environment that suits them best: Social areas, quiet andsilent areas.A wide range of online information sources, including eBooks, e-journals and subject databasesAcademic skills support via the Skills for Learning programmeStudents on campus can attend workshops or ask for one-to-one help on a range of skills such asacademic writing and referencing.Dedicated Subject Pages to enable you to explore key online information sources that are recommendedfor their studies.Physical access to local libraries both in UK and overseas via SCONUL and WorldCat agreements

http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/quality-code-part-a

http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/qualifications

http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/characteristics-statements

http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/academic-credit

http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/subject-benchmark-statements

http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/quality-code-part-b

http://www.wlv.ac.uk/about-us/governance/legal-information/policies-and-regulations/academic-regulations/

We also strongly advise you to download to “MyWLV” student app. MyWLV is a single point of personalisedaccess to the variety of systems the University offers. This includes pulling through relevant information (e.g.deadlines, timetables) and linking to underlying systems.

Leave of Absence:

The University allows breaks in learning of up to two years and there is a process for applying for a leave ofabsence, which can be accessed through your e:Vision account. Initially you will need to apply for the leave ofabsence, which could be for medical, parental or personal reasons. A short-term absence, such as annual leave,must not be recorded as a break. The course leader will consider, and where appropriate agree, the leave ofabsence application. A return date will be identified and agreed for a suitable point in the programme.Additional course fees may be incurred as a result of a leave of absence and you are advised to discuss thiswith the Faculty Student Services team prior to application.

Course Specific Support

General University support:

University Learning Centres are the key source of academic information for students. Learning Centresprovide physical library resources (books, journal, DVDs etc.) and offer a range of study areas to allowstudents to study in the environment that suit them best: Social areas, quiet and silent areas. Learning Centresalso provide access to wide range of online information sources, including eBooks, e-Journals and subjectdatabases.

Learning Centres also provide students with academic skills support via the Skills for Learning programme.Students on campus can attend workshops or ask for one-to-one help on a range of skills such as academicwriting and referencing. Students can access a range of online skills material at: www.wlv.ac.uk/lib/skills

The University Student Support website offers advice on a variety of matters (careers, counselling, studentunion advice, etc.) Students can also access these services by booking appointment with the SU, careers,counselling services, etc.

Course Specific Support

At the start of each year of your course you will be assigned a Personal Tutor who will guide you through theinduction process and provide support and academic counselling throughout the year on an appointmentbasis. They should be able to offer you advice and guidance to help you liaise with other staff and supportfacilities in the School and University. You should meet your Personal Tutor at least 3 times a year, whichmust include meetings that you are invited at critical points in your course.

The Faculty Students Services Office (FSSO) provides academic support (along with tutors) and will beaccessible throughout the week on an appointment basis to discuss timetables, requests for extensions,requests for extenuating circumstances, general concerns about study and student life and generalprogramme planning. The FSSO will act as a first point of contact in relation to leave of absence (includingreturning after leave), withdrawal, transferring to another course (internal and external) and changes to modeof attendance. Your Course Leader will also be available thereafter for meetings by appointment (throughSAMS) to discuss leave of absence, withdrawal, transferring to another course (internal and external), changesto mode of attendance, returning after leave of absence and direct entrants.

Subject support:

Tutorials, workshops, seminars and meetings - provide the primary opportunities for students to interact withstaff on topics relating to modules. All modules provide at least one of these forms of face-to-face support.

Formative feedback - tutors provide personalised written feedback on most summative assessments. Themechanism for feedback from purely formative tasks varies between assessments, but will always beprovided in some form. Online formative tasks often provide feedback straight away. On occasions tutors mayprovide generalised verbal feedback to the whole class on points relating to an assessment

http://www.wlv.ac.uk/lib/info/welcome

http://www.wlv.ac.uk/lib/skills-for-learning/

https://www.wlv.ac.uk/study-here/student-support

Assessment and subject-based surgeries provide additional student support for subjects that students oftenneed extra help with. They are often concentrated around the times when assessments take place. Revisionsessions are provided for many modules that have exam-like tests and enable you to interact with tutors toreview parts of the course. Mock exams and tests may provide opportunities to experience an examinationenvironment before the final summative test and give you feedback on your understanding.

Contact Hours

In higher education, the term ‘contact hours’ is used very broadly, to refer to the amount of time that youspend learning in contact with teaching or associated staff, when studying for a particular course.

This time provides you with the support in developing your subject knowledge and skills, and opportunitiesto develop and reflect on your own, independent learning. Contact time can take a wide variety of formsdepending on your subject, as well as where and how you are studying. Some of the most common examplesare:

lecturesseminarstutorialsproject supervisionsdemonstrationspractical classes and workshopssupervised time in a studio/workshopfieldworkexternal visitswork-based learning (including placements)scheduled virtual interaction with tutor such as on line, skype, telephone

In UK higher education, you as the student take primary responsibility for your own learning. In this context,contact time with teaching and associated staff is there to help shape and guide your studies. It may be usedto introduce new ideas and equip you with certain knowledge or skills, demonstrate practical skills for you topractise independently, offer guidance on project work, or to provide personalised feedback.

Alongside contact time, private or independent study is therefore very significant. This is the time that youspend learning without direct supervision from, or contact with, a member of staff. It might includebackground reading, preparation for seminars or tutorials, follow-up work, wider practice, the completion ofassignments, revision, and so on.

50 Day Engagement:

You will be withdrawn from the University if you fail to engage with the academic requirements of yourcourse of study, within 50 days of the course start date, following repeated and reasonable attempts by theUniversity to contact you.

Course Specific Health and Safety Issues

Course Specific Health and Safety Issues: All students in the faculty of Science and Engineering are requiredto take and pass their Schools/Departments Health and Safety Assessment. All assessments are available viathe Faculty of Science and Engineering Student Information topic in Canvashttps://canvas.wlv.ac.uk/courses/9679 and you will only be allowed to carry out any practical work once youhave passed the relevant assessments. It is essential that you read and understand the relevant codes coveringthe work within your specialist area and that you check them regularly for updates. All assessments shouldbe completed before teaching commences.

Any student who currently has access to a restricted area, such as the Rosalind Franklin Building, via their IDcard will have their access revoked at the start of the academic year unless they have passed their

https://canvas.wlv.ac.uk/courses/9679

Schools/Departments Health and Safety Assessment. Students should be aware that any attempt to bypassthe security systems can lead to disciplinary action.

Course Fact File

Hierarchy of Awards:Hierarchy of Awards: Bachelor of Science with Honours Artificial Intelligence and Robotics with SandwichPlacement Bachelor of Science Artificial Intelligence and Robotics with Sandwich Placement Bachelor of Science with Honours Artificial Intelligence and Robotics Diploma of Higher Education Artificial Intelligence and Robotics Certificate of Higher Education Artificial Intelligence and Robotics University Statement of Credit University Statement of Credit

Course Codes:Course Codes: CS025K23UV Sandwich 4 Years

UCAS Code:UCAS Code: GH77

Awarding Body / Institution:Awarding Body / Institution: University of Wolverhampton

School / Institute:School / Institute: School of Mathematics and Computer Science

Category of Partnership:Category of Partnership: Not delivered in partnership

Location of Delivery:Location of Delivery: University of Wolverhampton

Teaching Institution:Teaching Institution: University of Wolverhampton

Published: 09-Jul-2018 by Sarah I. Slater

course guide bsc (hons) artificial intelligence and robotics

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