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.

What you will study

• 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.