Full time 12 Month(s)
Computer science is a dynamic discipline, applicable to a diverse range of industries. This Masters programme explores cutting-edge innovation in experimental computer science, and provides you with a solid grounding of professional, real-world experience.
Our MSc Computer Science programme has been designed specifically to meet the needs of contemporary industrial and research environments. As a result, this programme blends advanced academic teaching with rigorous practical and professional experience. This will ensure you have the skills, knowledge, and awareness to engage with computing and computer science in a vast range of industries.
Your study will be based in InfoLab21, our world-class ICT Centre of Excellence. Here you will engage with seven taught modules and a research or industry placement. These modules will provide you with a wealth of specialist knowledge and skills, covering a range of topics informed by our research excellence. Topics include: Distributed Systems; Advanced Human Computer Interaction; and Systems Architecture and Integration.
In addition to these taught modules, you will undertake a substantial independent research project, supervised by a member of academic staff. Your project will tackle a real-world problem that you have identified, and will allow you to apply your technical skills and knowledge to current world-class research. You will also develop expert knowledge of a specific area of the discipline. Over the course of your project, you will also practise your ability to identify and structure research questions; gather, analyse and evaluate data and evidence; and present and communicate your findings and conclusions.
Finally, during the MSc programme, you will develop relevant work skills and will have the opportunity to engage with industry. Our programme leads to fantastic graduate prospects and will ensure you are well placed to pursue these options. You will gain real-world, applicable work experience by working with one of our partner companies, providing you with insight into a professional ICT environment. You will also have access to our Knowledge Business Centre (KBC), a place of business collaboration based in InfoLab21, which provides you with a direct link to over 500 ICT-centric organisations.
You will study a range of modules as part of your course, some examples of which are listed below.
This module will equip students with the ability to develop and apply a deep understanding of fundamental principles, techniques and technologies that underpin today's global IT infrastructure. They will learn to assess new systems technologies, to know where technologies fit in a comprehensive schema, and to know what to read in order to develop a deeper level of understanding. Students will focus on the properties of system components, and will become familiar with the strengths, weaknesses, scalability and bottlenecks of systems components. This will enable them to make intelligent and well-reasoned trade-offs between fundamental building blocks of distributed systems in today’s IT infrastructure.
This is a highly practical module, in which students build a major system representative of an end-to-end IT infrastructure, and is also highly discussion-oriented, with frequent in-class discussion sections and problem-solving group work. The module covers a very broad range of state-of-the-art techniques and principles of modern distributed systems. These including: caching, tiering, replication, synchronisation, failure and reliability. Students will also explore real-world technologies, from interaction paradigms in distributed systems, to peer-to-peer architectures and scalable and high-performance networking and storage.
Explore advanced topics in experimental Human-Computer Interaction (HCI), such as understanding users and their requirements, investigating design spaces and prototyping and developing innovative interaction techniques. The module offers increased experience in HCI literature and design methods both with and without users, as well as practical experience of using supporting tools. Students will learn about modelling techniques and design space techniques as part of the module.
Upon completion of the module, students will have the knowledge to conduct experimental HCI research and have the motivation, experience and tools for understanding users and their requirements for interaction. The module helps to develop scientific writing skills and analytical thinking and prepares students for further postgraduate study, or for a successful career in IT or computing.
Students are provided with a comprehensive coverage of the problems related to data representation, manipulation and processing in terms of extracting information from data, including big data. They will apply their working understanding to the data primer, data processing and classification. They will also enhance their familiarity with dynamic data space partitioning, using evolving, clustering and data clouds, and monitoring the quality of the self-learning system online.
Students will also gain the ability to develop software scripts that implement advanced data representation and processing, and demonstrate their impact on performance. In addition, they will develop a working knowledge in listing, explaining and generalising the trade-offs of performance, as well as the complexity in designing practical solutions for problems of data representation and processing in terms of storage, time and computing power.
Introducing a range of architectural approaches, techniques and technologies that underpin today’s global IT infrastructure, this module combines with other modules to form the systems stream of the programme. It is designed to enhance students’ knowledge of how building blocks are composed to create systems of systems.
Students will gain a detailed understanding and an ability to critique contemporary systems’ architecture in terms of scalability, resilience, performance and other shortcomings.
The principal ethos of this module is to focus on the principles, emergent properties and the application of systems elements as used in large-scale and high performance systems. Detailed studies and invited industrial speakers will be used to provide supporting real-world context and a basis for seminar discussions. Students are also offered ‘hands-on’ measurement-based coursework that focuses on the scalability of a significant technology.
This module covers advanced topics in experimental Human-Computer Interaction (HCI) with an emphasis on experimental design, evaluation methodologies, statistical analysis and result interpretation. Whilst engaging with a number of key topics, students will be asked to explore the evaluation process. Students will learn to recognise when HCI is required and which forms of evaluation is necessary in a given situation, for example making appropriate selections from systems vs user and qualitative vs quantitative evaluations.
Practical sessions will enable students to develop skills with statistical analysis packages. They will also receive guidance on the application of appropriate tests and result reporting.
This module provides students with up-to-date information on current applications of data in both industry and research. Expanding on the module ‘Fundamentals of Data’, students will gain a more detailed level of understanding about how data is processed and applied on a large scale across a variety of different areas.
Students will develop knowledge in different areas of science and will recognise their relation to big data, in addition to understanding how large-scale challenges are being addressed with current state-of-the-art techniques. The module will provide recommendations on the Social Web and their roots in social network theory and analysis, in addition their adaption and extension to large-scale problems, by focusing on primer, user-generated content and crowd-sourced data, social networks (theories, analysis), recommendation (collaborative filtering, content recommendation challenges, and friend recommendation/link prediction).
On completion of this module, students will be able to create scalable solutions to problems involving data from the semantic, social and scientific web, in addition to abilities gained in processing networks and performing of network analysis in order to identify key factors in information flow.
Submission Date: end of August
A large part of the masters involves completing a dissertation project. This starts with students selecting a project by December in the first year of study. This piece of work will involve writing 40000 words and at least 200 hours of work.
This is primarily a self-study module that is designed to provide the foundation of the main dissertation, at a level considered to be publishable quality. On completion of this module, students are expected to be able to make value judgement relating to technologies and applications, and to justify these to peers and academic staff.
The topic of the project will vary from student to student, but will be at a level commensurate with the weight and level of the module. Students will refine, extend, and perfect their own scientific reflection and practice. The project also offers students the opportunity to apply their technical skills and knowledge on currrent world-class research problems and to develop an expert knowledge of a specific area.
Students will gain a formal understanding of research and will develop the ability to critically reflect on research approaches and practices in the field of computing. Research Methods will also encourage an appreciation of the different ways that other disciplines, academic communities and industries all conduct research. There will be an opportunity to plan a research project and develop a convincing study design to address a challenge or problem. This module explores ethical and data management issues associated with research as well as research and innovation practices in industry.
The module covers the fundamentals of research such as sampling and design, before considering strategies and research methods. Furthermore, the module offers greater insight into research design, such as how to structure and frame research studies, choosing a research strategy and selecting the best research method. Students will learn about ethical issues in research and approval processes before understanding the opportunities and expectations from their industrial placements.
Information contained on the website with respect to modules is correct at the time of publication, but changes may be necessary, for example as a result of student feedback, Professional Statutory and Regulatory Bodies' (PSRB) requirements, staff changes, and new research.
Director of Studies: Dr Barry Porter
Designed for: Those looking for a career in software development and software engineering, programming, computer science research, or a related computer science discipline.
Entry requirements: High 2:2 (Hons) degree (UK) or equivalent in Computer Science or similar degrees. Your degree should have covered the following modules:
If you have studied outside of the UK, you can check your qualification here: International Qualifications
We may consider non-standard applicants, please contact us for further information.
IELTS (Academic): Overall score of at least 6.5, with no individual element below 6.0
We consider tests from other providers, which can be found here: English language requirements
If your score is below our requirements we may consider you for one of our pre-sessional English language programmes:
10 week - Overall score of at least 5.5, with no individual element below 5.0
For details of eligibility see: Pre-sessional programmes
4 week - Overall score of at least 6.0, with no individual element below 5.5
Further information is available at English for Academic Purposes
Assessment: Coursework, presentations, class tests and a dissertation
Funding: All applicants should consult our information on Fees and Funding.
Further information: Please see our website
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