MSc Computer Science

Computer science is one of the fastest growing subjects around the world. From its theoretical and algorithmic foundations to cutting-edge development in robotics and intelligent systems, it is a wide field which needs an increasing number of suitably educated individuals to support it.

This computer science masters introduces you to a number of software and hardware technologies and their real world applications.

You’ll learn about abstraction, complexity, evolutionary change, sharing of common resources, security and concurrency.

From system functionality to usability and performance, you’ll also be better placed to solve real-life problems with an understanding of how they affect people’s lives.

This course is subject to validation.

Study Mode
2019
Duration Start Date Campus Campus Code
Full-time 1 Year September Treforest A
Part-time 2 Years September Treforest A

Object Oriented Programming with Data Structures and Algorithms – 40 credits
Object Oriented Programming with Data Structures and Algorithms provides students with opportunity to obtain advanced knowledge and practical skills in the analysis, synthesis, design and implementation of advanced algorithms and data structures. Students will gain skills in Implementation and performance analysis of advanced data structures such as: Queues, B-trees, Oct-tree, Quad-trees, AVL, binary space partitioning grids or multi-resolution maps.

Data Mining – 20 credits
Data Mining provides students with opportunity to appreciate the value of data mining in solving real-world problems by conveying foundational concepts of data mining, big data, and data analytics. Students will gain knowledge of key concepts, algorithms, and techniques commonly used in data mining and big data tools for collection and analysis of data sets.

Distributed Computing – 20 credits
Distributed Computing provides students with opportunity to gain a detailed understanding of the underlying principles associated with distributed computer systems, both from an academic and commercial perspective. Students will work on Developing simulations to demonstrate understanding of distributed system environments and well as cover issues surrounding distributed privacy and security.

 

Project Management and Research Methodology – 20 credits
Project Management and Research Methodology provides students with the opportunity to plan a project using appropriate methods, techniques and tools, taking into account relevant risks and ethical issues, and undertake a literature review and other development activities to improve their understanding of the situation and/or produce organisational change.

Robotics – 20 credits (optional)
Robotics provides students with opportunity to develop analytic and practical skills in the design and critical evaluation of the elements of a robotic system also to demonstrate the ability to specify and appraise robotic and agent-based systems. Students will cover concepts such as advanced architectures for robot control robot vision and navigation as well as advanced (and low level) robotics design, analysis and implementation/

Mobile Application Development – 20 credits (optional)
Mobile Application Development provides students with opportunity to demonstrate the application of the theoretical and practical knowledge of the technologies associated with building robust distributed network-based mobile applications. Students will get to further develop skills in designing, implementing, testing and critically evaluating mobile technologies and robust distributed network-based mobile applications

Intelligent Systems – 20 credits (optional)
Intelligent Systems provides students with opportunity to provide a broad theoretical and practical introduction to applicable artificial intelligence and the design and development of intelligent systems. Students will cover concepts such as knowledge representation and reasoning, machine learning and multi-agent systems.

MSc Project – 60 credits
The highlight of the course for many students is the individual project, undertaken under the supervision of one of the lecturing team, where they get to apply what they have learned to a scenario that is complex and demanding.

Teaching

This postgraduate computing course is delivered in four major blocks to offer an intensive but focused learning pattern. Full-time students will typically spend 12 hours in classes and 24 hours outside of classes each week.

If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects.

You will need to spend a significant amount of time working independently, reading and preparing for assessments. Assessment is primarily by coursework, varying from a research-style paper or essay to practical assignments.

You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.

 

Assessment

Assessment is primarily by coursework (94%), varying from a research-style paper or essay to practical assignments.

You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.

Placements

Through the Erasmus scheme, students could have the opportunity to attend summer schools in advanced computer vision and machine learning with our partners in TEI of Crete, University of Patras, University of Burgundy, Cyprus University of Technology, Polytechnic Institute of Porto and the University of Salento.

Facilities

Practice is so important in gaining understanding of complex machine learning techniques, which is why we have a range of high specification computer laboratories including workrooms dedicated to our masters’ students.

These facilitate a learning environment where you can work individually or in groups and as they are located close to the staff offices.

Our facilities are at the cutting edge of computer development, meaning you’ll use the latest technologies in high-spec labs.

You’ll also find dedicated spaces on campus for computing students, including Windows, Apple Mac, Linux and Networking suites, all with the latest software.

Lecturers

A dedicated team of experienced teachers with a wide range of industrial and research backgrounds teach on our computing courses at the University of South Wales.

These varied backgrounds help ensure that students not only learn about technologies and methodologies that are at the vanguard of computer science but gain knowledge about how they are applied. 

This course is designed for graduates with a minimum 2:2 Honours degree or equivalent in a computing or strongly related subject.

Applicants should be proficient programmers.

International Entry Requirements

This course welcomes international applicants and requires an English level of IELTS 6.0 with a minimum of 5.5 in each component or equivalent.

Full-time fees are per year. Part-time fees are per 20 credits. Once enrolled, the fee will remain at the same rate throughout the duration of your study on this course.

August 2019 – July 2020 Fees: USW will be offering a package of financial support for postgraduate study and this will be announced shortly.

August 2019 - July 2020 Fees


  • Full-time UK and EU:  £9000

  • Full-time International:  £13400 

  • Part-time UK and EU:  £1000 per 20 credits

Additional Costs

Students have access to a wide range of resources including textbooks, publications, and computers in the University’s library and via online resources. In most cases they are more than sufficient to complete a course of study. Where there are additional costs, either obligatory or optional, these are detailed below. Of course students may choose to purchase their own additional personal resources/tools over and above those listed to support their studies at their own expense. All stationery and printing costs are at a student’s own expense.

Graduates with an MSc Computer Science will be suitable for roles in software development, database administration, computer hardware engineering, computer systems analysis, computer network architecture, web development, information security analysis, computer programming and computer networks.

Students who complete computing masters will be educated to a professional standard in a range of fields related to computer science, and will have improved transferable skills including problem solving, communication, team working, effective use of IT facilities and information retrieval.

With training to Masters level now the recognised professional level of competence, graduates will be better placed to pursue careers in industry, or continue their interest in computer science through research at PhD level.

Our Careers and Employability Service

As a USW student, you will have access to advice from the Careers and Employability Service throughout your studies and after you graduate.

This includes: one-to-one appointments from faculty based Career Advisers, in person, over the phone or even on Skype and through email via the "Ask a Question" service. We also have extensive online resources for help with considering your career options and presenting yourself well to employers. Resources include psychometric tests, career assessments, a CV builder, interview simulator and application help. Our employer database has over 2,000 registered employers targeting USW students, you can receive weekly email alerts for jobs.

Our Careers service has dedicated teams: A central work experience team to help you find relevant placements; an employability development team which includes an employability programme called Grad Edge; and an Enterprise team focused on new business ideas and entrepreneurship.