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Course content

The demand for better products and commercial services drives the search for creative solutions using computing-based systems, and has established a critical dependence between computing and practically every industry and sector. This flexible programme offers a broad range of advanced study options, reflecting the emerging technologies in industry.

You will be able to shape your programme to match your interests and career ambitions, choosing modules from a range of areas, including the development of human-computer communications (dialogue systems), ubiquitous computing, applying interactive digital multimedia techniques, security and surveillance, and building decision-support tools for uncertain problems in various contexts (e.g. legal, medical, safety). This is a multidisciplinary programme and, in addition to pure computer science modules, you may choose options where computer science intersects with other fields and builds on your first degree.

This programme will:

  • Allow you to personalise your programme through a wide range of employment-relevant module choices.
  • Build your links with industry and potential employers - we have excellent links with industry, working together on commercial and research projects.

Why study your MSc in Computer Science at Queen Mary?

Our research-led approach

Your tuition will be delivered by field leading academics engaged in world class research projects in collaboration with industry, external institutions and research councils.

Our strong links with industry

  • We have collaborations, partnerships, industrial placement schemes and public engagement programmes with a variety of organisations, including Vodafone, Google, IBM, BT, NASA, BBC and Microsoft.
  • Full-time MSc with Industrial Experience option available on our taught MSc programmes. You have the option to complete over two years, with a year of work experience in industry.
  • Industrial projects scheme - To support industrial experience development, you can do your final project in collaboration with an industrial partner.

Full-time

Undertaking a masters programme is a serious commitment, with weekly contact hours being in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.

Part-time

Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.

Important note regarding Part Time Study

We regret that, due to complex timetabling constraints, we are not able to guarantee that lectures and labs for part time students will be limited to two days per week, neither do we currently support any evening classes. If you have specific enquiries about the timetabling of part time courses, please contact the MSc Administrator.

Structure

MSc Computer Science is currently available for one year full-time study, two years part-time study.

Semester 1 - (Maximum of 4 modules to be taken in Semester 1)

Select at least one from:

  •  Functional Programming
  •  Semi-Structured Data and Advanced Data Modelling
  •  Introduction to Object-Oriented Programming

Further options:

  • Machine Learning
  • Introduction to Computer Vision
  • Design for Human Interaction
  • Program Specifications
  • Big Data Processing
  • Introduction to Law for Science and Engineering

Semester 2 - (Maximum of 4 modules to be taken in Semester 2)

Select at least one from:

  •  Security and Authentication 
  •  Interactive Systems Design
  •  Bayesian Decision and Risk Analysis 

Further options from:

  •  Mobile Services
  •  Real Time & Critical Systems
  •  Business Technology Strategy
  •  The Semantic Web
  •  Information Retrieval
  •  Software Analysis and Verification
  •  Natural Language Processing
  •  Advanced Object Oriented Programming
  •  Cloud Computing
  •  Data Analytics
  •  Parallel Computing
  •  Machine Learning for Visual Data Analytics
  • Foundations of Intellectual Property Law and Management

Semester 3

  •  Project

Please note that elective modules are subject to availability, timetabling constraints and may be subject to change.


Visit the MSc Computer Science page on the Queen Mary University of London website for more details!

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