MSc Advanced Computing Science

This Advanced Computing Science Masters allows you to deepen your knowledge of the subject, drawing on the expertise of our world-leading academics to investigate topics at the cutting edge of Computing research.

The MSc is designed for graduates with a Computing Science background who wish to study new topics, begin to specialise in a particular field, and gain further qualifications. It’s ideal as preparation for a research post or for graduates looking to differentiate themselves in the job market.

The degree is more flexible than some our more specialised courses and gives you the choice of a wide range of topics, reflecting the research specialisms of our School – including Artificial Intelligence, Graphics, Audio and Visual Processing, Data Mining and Systems Engineering. You’ll become aligned with one of our major research areas and undertake an in-depth project that may involve a placement with one of our industry links.

Overview

This degree follows the same programme as its full-time equivalent but is spread over two years. A study plan should be discussed with the course director.

Course Modules

Students must study the following modules for 40 credits:

Name Code Credits

ADVANCED PROGRAMMING CONCEPTS AND TECHNIQUES

This module starts off with state of the art software engineering concepts including the Unified Process (UP) as part of Iterative and Incremental Development (IID), Agile Programming methods (e.g. extreme programming, scrum, etc.), and Design Patterns. This is followed by covering advanced features of three of the currently most popular General Purpose Languages (GPL's): C++, Java and C#. Different IDE's are covered in depth (such as Visual Studio, netbeans and Eclipse). Other advanced programming concepts include dynamic link libraries (DLL's), GPU based API's (Application Programming Interfaces) such as CUDA and OpenCL, exception handling, memory management and multithreading.

CMP-7009A

20

RESEARCH TECHNIQUES (RESEARCH METHODS)

This module aims to prepare postgraduate students with necessary intellectual and practical skills for successfully carrying out research work for their MSc Dissertation in Computing Sciences and Computational Biology. Specifically, it teaches research methodologies, techniques and tools used in computing sciences, and more importantly, provides systematic trainings to enhance students' transferable skills and their understanding in ethics, social and legal issues involved in computing professions.

CMP-7030Y

20

Students will select credits from the following modules:

Students will select 20-40 credits from the following modules:

Name Code Credits

ARTIFICIAL INTELLIGENCE

This module introduces the students to core techniques in Artificial Intelligence and some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.

CMP-7028A

20

COMPUTER GAMES LABORATORY

The module is seminar- and lab-based and draws on previous knowledge of 3D computer graphics programming (for example CMP-7013A/CMP-6006A). It aims to make the student familiar with more advanced computer graphics and games methodologies and technologies. This includes Virtual Reality (VR), Augmented Reality (AR), Motion Capture, Haptic and Force Feedback and Stereoscopy. Seminars also cover advanced topics such as physics simulation, physics engines, games Artificial Intelligence (AI), mobile games development, character animation, procedural content generation (PCG) and serious games (medical and other applications).

CMP-7014B

20

COMPUTER GRAPHICS

This module covers the fundamentals in 3D graphics including transformations, lighting, shading, texture mapping and anti-aliasing techniques. The module also provides an introduction to programming 3D graphics using OpenGL and the OpenGL Shading Language (GLSL). Ability to program in a high level language such as C++ or Java is required. This module should not be taken if you have previously taken CMP-6006A.

CMP-7013A

20

DATA MINING

This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

DISTRIBUTED COMPUTING

Single computer systems have limited processing power and are vulnerable to failure. Using distributed computing, processing speeds exceeding the limits of any single computer, and systems that continue to be available when individual computers fail can be realised. Achieving these features requires use of adequate algorithms, software architectures and networking techniques. This is the subject of this module.

CMP-7010B

20

HUMAN COMPUTER INTERACTION

An overview of Human Computer Interaction, including user interfaces on conventional computers and small footprint devices (e.g. smartphones). Human-Computer interactions are approached from a variety of perspectives, with an emphasis on experimental evaluation.

CMP-7018A

20

Students will select 20 credits from the following modules:

Name Code Credits

APPLIED STATISTICS

This is a module designed to give students the opportunity to apply statistical methods in realistic situations. While no advanced knowledge of probability and statistics is required, we expect students to have some background in probability and statistics before taking this module. The aim is to introduce students to R statistical language and to cover Regression, Analysis of Variance and Survival analysis. Other topics from a list including: Extremes and quartiles, Bootstrap methods and their application, Sample surveys, Simulations, Subjective statistics, Forecasting and Clustering methods, may be offered to cover the interests of those in the class. BEFORE TAKING THIS MODULE you have taken CMP-4004Y or CMP-4005Y or CMP-4006Y or have an equivalent basic knowledge of probability and statistics.

CMP-7008B

20

ARTIFICIAL INTELLIGENCE

This module introduces the students to core techniques in Artificial Intelligence and some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.

CMP-7028A

20

AUDIO AND VISUAL PROCESSING

CMP-7016A

20

COMPUTER GAMES LABORATORY

The module is seminar- and lab-based and draws on previous knowledge of 3D computer graphics programming (for example CMP-7013A/CMP-6006A). It aims to make the student familiar with more advanced computer graphics and games methodologies and technologies. This includes Virtual Reality (VR), Augmented Reality (AR), Motion Capture, Haptic and Force Feedback and Stereoscopy. Seminars also cover advanced topics such as physics simulation, physics engines, games Artificial Intelligence (AI), mobile games development, character animation, procedural content generation (PCG) and serious games (medical and other applications).

CMP-7014B

20

COMPUTER GRAPHICS

This module covers the fundamentals in 3D graphics including transformations, lighting, shading, texture mapping and anti-aliasing techniques. The module also provides an introduction to programming 3D graphics using OpenGL and the OpenGL Shading Language (GLSL). Ability to program in a high level language such as C++ or Java is required. This module should not be taken if you have previously taken CMP-6006A.

CMP-7013A

20

COMPUTER VISION

Computer Vision is about "teaching machines how to see". It includes methods for acquiring, analysing and understanding images. The unit comprises lectures and laboratories. Practical exercises and projects, undertaken in the laboratory support the underpinning theory and enable students to implement contemporary computer vision algorithms.

CMP-7026B

20

DATA MINING

This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

DISTRIBUTED COMPUTING

Single computer systems have limited processing power and are vulnerable to failure. Using distributed computing, processing speeds exceeding the limits of any single computer, and systems that continue to be available when individual computers fail can be realised. Achieving these features requires use of adequate algorithms, software architectures and networking techniques. This is the subject of this module.

CMP-7010B

20

HUMAN COMPUTER INTERACTION

An overview of Human Computer Interaction, including user interfaces on conventional computers and small footprint devices (e.g. smartphones). Human-Computer interactions are approached from a variety of perspectives, with an emphasis on experimental evaluation.

CMP-7018A

20

INFORMATION VISUALISATION

This module is an introduction to information visualization. It covers techniques for summarizing and presenting a wide range of data. The problems and techniques for dealing with large data flows are a major theme and there is a strong emphasis on understanding the appropriate context and use of visualization techniques.

CMP-7022B

20

INTERNET and MULTIMEDIA TECHNIQUES

This module surveys the current and emerging technologies of the Internet and its impact on society, particularly e-commerce. The practical part of the module concentrates on the design and integration of web sites, using a range of tools and techniques in current use.

CMP-7003A

20

MODERN EMBEDDED TECHNOLOGY

Embedded processors are at the core of a huge range of products e.g. mobile telephones, cameras, passenger cars, washing machines, DVD players, medical equipment, etc. The embedded market is currently estimated to be worth around 100x the 'desktop' market and is projected to grow exponentially over the next decode. This module considers the design and development of real-time embedded system applications for commercial off the shelf (COTS) processors running real time operating systems (RTOS) such as ARM-RT, uCLinux etc.

CMP-7029B

20

SYSTEMS ENGINEERING ISSUES

This module draws together a wide range of material and considers it in the context of developing modern large-scale computer systems. Topics such as Outsourcing, Process Improvement, System Failure, Project Management, Configuration Management, Maintainability, Legacy Systems and Re-engineering, Acceptance and Performance Testing, Metrics and Human Factors are covered in this module. The module is supported by a series of industrial case studies and includes speakers from industry.

CMP-7004B

20

Students must study the following modules for 60 credits:

Name Code Credits

DISSERTATION

In this module, each Masters student is required to carry out project work with substantial research and practical elements on a specified topic for their MSc dissertation from January to late August. The topic can be chosen and allocated from the lists of proposals from faculty members, or proposed by students themselves with an agreement from their supervisor and also an approval from the module organiser. The work may be undertaken as part of a large collaborative or group project. A dissertation must be written as the outcome of the module.

CMP-7027X

60

Students will select credits from the following modules:

Students will select 20-40 credits from the following modules:

Name Code Credits

APPLIED STATISTICS

This is a module designed to give students the opportunity to apply statistical methods in realistic situations. While no advanced knowledge of probability and statistics is required, we expect students to have some background in probability and statistics before taking this module. The aim is to introduce students to R statistical language and to cover Regression, Analysis of Variance and Survival analysis. Other topics from a list including: Extremes and quartiles, Bootstrap methods and their application, Sample surveys, Simulations, Subjective statistics, Forecasting and Clustering methods, may be offered to cover the interests of those in the class. BEFORE TAKING THIS MODULE you have taken CMP-4004Y or CMP-4005Y or CMP-4006Y or have an equivalent basic knowledge of probability and statistics.

CMP-7008B

20

ARTIFICIAL INTELLIGENCE

This module introduces the students to core techniques in Artificial Intelligence and some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.

CMP-7028A

20

AUDIO AND VISUAL PROCESSING

CMP-7016A

20

COMPUTER GAMES LABORATORY

The module is seminar- and lab-based and draws on previous knowledge of 3D computer graphics programming (for example CMP-7013A/CMP-6006A). It aims to make the student familiar with more advanced computer graphics and games methodologies and technologies. This includes Virtual Reality (VR), Augmented Reality (AR), Motion Capture, Haptic and Force Feedback and Stereoscopy. Seminars also cover advanced topics such as physics simulation, physics engines, games Artificial Intelligence (AI), mobile games development, character animation, procedural content generation (PCG) and serious games (medical and other applications).

CMP-7014B

20

COMPUTER GRAPHICS

This module covers the fundamentals in 3D graphics including transformations, lighting, shading, texture mapping and anti-aliasing techniques. The module also provides an introduction to programming 3D graphics using OpenGL and the OpenGL Shading Language (GLSL). Ability to program in a high level language such as C++ or Java is required. This module should not be taken if you have previously taken CMP-6006A.

CMP-7013A

20

COMPUTER VISION

Computer Vision is about "teaching machines how to see". It includes methods for acquiring, analysing and understanding images. The unit comprises lectures and laboratories. Practical exercises and projects, undertaken in the laboratory support the underpinning theory and enable students to implement contemporary computer vision algorithms.

CMP-7026B

20

DATA MINING

This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

CMP-7023B

20

DISTRIBUTED COMPUTING

Single computer systems have limited processing power and are vulnerable to failure. Using distributed computing, processing speeds exceeding the limits of any single computer, and systems that continue to be available when individual computers fail can be realised. Achieving these features requires use of adequate algorithms, software architectures and networking techniques. This is the subject of this module.

CMP-7010B

20

HUMAN COMPUTER INTERACTION

An overview of Human Computer Interaction, including user interfaces on conventional computers and small footprint devices (e.g. smartphones). Human-Computer interactions are approached from a variety of perspectives, with an emphasis on experimental evaluation.

CMP-7018A

20

INTERNET and MULTIMEDIA TECHNIQUES

This module surveys the current and emerging technologies of the Internet and its impact on society, particularly e-commerce. The practical part of the module concentrates on the design and integration of web sites, using a range of tools and techniques in current use.

CMP-7003A

20

MODERN EMBEDDED TECHNOLOGY

Embedded processors are at the core of a huge range of products e.g. mobile telephones, cameras, passenger cars, washing machines, DVD players, medical equipment, etc. The embedded market is currently estimated to be worth around 100x the 'desktop' market and is projected to grow exponentially over the next decode. This module considers the design and development of real-time embedded system applications for commercial off the shelf (COTS) processors running real time operating systems (RTOS) such as ARM-RT, uCLinux etc.

CMP-7029B

20

SYSTEMS ENGINEERING ISSUES

This module draws together a wide range of material and considers it in the context of developing modern large-scale computer systems. Topics such as Outsourcing, Process Improvement, System Failure, Project Management, Configuration Management, Maintainability, Legacy Systems and Re-engineering, Acceptance and Performance Testing, Metrics and Human Factors are covered in this module. The module is supported by a series of industrial case studies and includes speakers from industry.

CMP-7004B

20

Disclaimer

Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules and regular (five-yearly) review of course programmes. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, there will normally be prior consultation of students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff or sabbatical leave. Where this is the case, the University will endeavour to inform students.

Entry Requirements

  • Degree Subject Computer Science or a related subject.
  • Degree Classification Good first degree (minimum 2.1 or equivalent).

Students for whom English is a Foreign language

We welcome applications from students whose first language is not English. To ensure such students benefit from postgraduate study, we require evidence of proficiency in English. Our usual entry requirements are as follows:

  • IELTS: 6.5 (minimum 6.0 in all components)
  • PTE (Pearson): 62 (minimum 55 in all components)

Test dates should be within two years of the course start date.

Other tests, including Cambridge English exams and the Trinity Integrated Skills in English are also accepted by the university. The full list of accepted tests can be found here: Accepted English Language Tests

INTO UEA also run pre-sessional courses which can be taken prior to the start of your course. For further information and to see if you qualify please contact intopre-sessional@uea.ac.uk

Fees and Funding

Tuition Fees for 2016/17

  • Home/EU:

     Full-time £7,150, Part-time £3,575

     If you choose to study part-time, please assume a pro-rata fee for the credits you are taking, or 50% of the equivalent fee per year if you are taking a full-time course on a part-time basis.  

  • Overseas:

      Full-time £14,500

      If you are classed as an 'overseas' student and are coming to UEA on a student or visitor's visa, UK visa rules won't normally allow you to study on a part-time course. You should always check with the UKVI for the latest requirement.

 

Scholarships

50% Final Year Undergraduate Continuation Scholarship

Current final year UEA undergraduate students who gain a First class degree and progress onto a postgraduate course in September 2016 will receive a 50% fee reduction scholarship. Who do not gain a First class degree will be eligible for the 10% UEA Alumni Scholarship outlined below. Terms and conditions apply.

 

UEA Alumni 10% Scholarship

A scholarship of 10% fee reduction is available to UEA Alumni looking to return for postgraduate study at UEA in September 2016. Terms and conditions apply.

How to Apply

 

Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.

You can apply online, or by downloading the application form.

Further Information

To request further information & to be kept up to date with news & events please use our online enquiry form.

If you would like to discuss your individual circumstances prior to applying please do contact us:

Postgraduate Admissions Office
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk

International candidates are also encouraged to access the International Students section of our website.

    Next Steps

    Need to know more? Take a look at these pages to discover more about Postgraduate opportunities at UEA…

    We can’t wait to hear from you. Just pop any questions about this course into the form below and our enquiries team will answer as soon as they can.

    Admissions enquiries:
    admissions@uea.ac.uk or
    telephone +44 (0)1603 591515