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MSc Computer Science

Course Overview

This course takes an immersive approach to learning both the principles and practices of computer systems with much of the material based around examples and practical exercises. Students completing this course will have a firm grasp of the current practices and directions in computer systems and will be able to design and build for example, distributed systems for the Web using Internet, Intranet and other technologies.

The objectives of this MSc are to provide the foundations for the understanding of core ideas, methods and technologies in computer science; to provide the technical skills and background material so that the postgraduate will be able to conduct a near state-of-the-art research or development project; to provide the graduate with a range of specialist and transferable skills & to provide the educational base for further professional development and lifelong learning.

Key information

    Course name

    MSc Computer Science

    Total academic credits

    180 credits

    Qualification awarded


    Awarding body

    Bangor University

    Professional recognition


    Academic level

    Postgraduate (QCF_NQF Level 7)

    Study mode

    Full time - Classroom


    12 months

    Tuition fees

    £13,800 (Scholarship available)



    Work placement


    Course location


Academic entry requirements

To be accepted onto this degree programme candidates should hold an Honours degree in Computer Science or a related scientific discipline, at a 2.2 level or higher or the international equivalent. Applicants with initial degrees in other disciplines will be considered on an individual basis, with the assessment based on the applicant’s potential to succeed on, and benefit from, the course.

English entry requirements

Graduates for whom English is not the first language must satisfy the University requirement for IELTS currently at 6.0 overall with no less than 5.5 in any band.

It may be necessary for applicants falling short of this minimum standard to attend an intensive English Language course before registering for the academic programme.

Assessment methods

Combination of examination, coursework and a supervised independent research project.

Progression route

Further postgraduate study (e.g. MSc by Research) or students can also continue onto MPhil or PhD by research that can lead to a career in higher education.

Career opportunities

The course programme will support graduates seeking careers as Database Administrator, Games Developer, Information Systems Manager, IT Consultant, Multimedia Programmer, Systems Analyst, System Developer, Web Designer, Web Developer etc.


Semester 1

  • Object Oriented Programming (15 credits)
  • Research Project Foundations (15 credits)
  • Information Visualization (15 credits)
  • Applied AI (15 credits)


Semester 2

  • Data Networks & Communications (15 credits)
  • Tech for Internet Systems (15 credits)
  • Distributed Systems (15 credits)
  • Virtual Environment & Human Perception (15 credits)


Semester 3

  • Comp-Project and Dissertation (60 credits) (semester 2)


Overall aims and purpose for choosing this course

  • To explore the fundamental principles of Object Oriented design and programming; to capitalise on the OO paradigm through encapsulation of advanced systems; to provide accelerated coverage of the Java programming language for graduates with a degree in Computer Science or related scientific discipline; to introduce a range of advanced programming tools and facilities; to read, use and write APIs to gain greater leverage from a language, e.g. JDBC, Multi-threading, GUI toolkits, Remote Method Invocation and Networking
  • To prepare the students for their MSc research project, including secondary research and primary research design, planning and execution via getting familiar with research tools and writing up a complete project proposal
  • While Scientific Visualization is the process of displaying scientific data, which is often spatial and has a direct association with our real world, Information Visualization (IV) focuses on the use of visualization techniques to help users understand and analyze non-scientific and abstract data. Such abstract data includes numerical data in tabular form, textual information and associative (network) sources, and contain multiple variables. The aim of this course is to introduce principles of information visualization, develop IV critiquing skills, learn about different Information Visualization designs, and gain foundational skills to design new innovative Information Visualization
  • To provide in-depth case studies in areas such as Internet systems, visualization, computer games, movie making, computer vision, and/or robotics to illustrate how methods and technologies developed for artificial intelligence and artificial life can be applied to real-world problems & to bridge the gap to ideas and developments at research level in applied artificial intelligence
  • To provide an in-depth understanding of how real communication networks are structured and the protocols that make them work. It will give the students an ability to explain in details the process followed to provide end to end connections and end-user services at required QoS
  • To discuss, critique and learn about the web development platform and highlight state of the art technologies and tools for Internet Systems. To plan, critique and develop interactive applications on the web-platform for the client, to focus on client-side scripting and direct integration with through the DOM to several W3C standards and discuss current technologies and future challenges for Internet Technologies
  • To introduce key ideas in Distributed Systems and its role and application in operating systems and middleware. For further information about the module, including full details of course content, assessment etc. please refer to the Module Descriptor. These can be found on the Interactive School Handbook, which is available from the School
  • To study the elements needed to build a Virtual Environment. To provide an overview of Human Perception and how it works. The technologies discussed will be illustrated by a series of state-of-the-art case studies
  • To provide advanced coverage of econometric methods and practices that are used to model financial and business data, and to develop a critical awareness of the strengths and limitations of modelling techniques
  • To conduct project work that is at near or actual state of the art research level and to present this work as a written dissertation