Qualification level
Study type
1 year full-time, 2 years part-time
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About the course

Course content

MSc Computer Science with Business combines core Computer Science modules with modules in Management, Strategy, Marketing and Accounting. This course is taught in partnership between the College of Engineering, Mathematics and Physical Sciences and the University of Exeter Business School. This blend of business and science is designed for students wanting management or leadership roles working with data.

You will be able to engage with the latest developments from a range of Computer Science topics with leading academics in the field. Course content draws directly upon our particular research strengths in artificial intelligence, machine learning, data science, high performance computing and networks, and cyber-security.

This MSc is career-focused, with an emphasis on postgraduate training. You will develop a wide range of important skills such as team-working, coding, independent research and problem solving. This course is suited to those looking to use their expertise commercially in any sector, particularly in management or leadership roles.

Your project, which forms a major part of the MSc, will maintain a business focus as you explore data science in a commercial environment.


Constituent modules and pathways may be updated, deleted or replaced in future years as a consequence of programme development. Details at any time may be obtained from the programme website.

The compulsory modules can include;

  • Group development project
  • Computer science business project

Optional modules can include;

  • Managing operations
  • Strategic innovation management
  • Strategy
  • Marketing Strategy
  • Accounting for international managers
  • Logic, ontology and knowledge representation
  • Nature-inspired computation
  • Research methodology
  • Machine learning and statistics
  • Evolutionary computation and optimisation
  • Computer modelling and simulation
  • Computer vision
  • From data to decisions
  • Data in business and society
  • High performance computing and data architectures
  • Social networks and text analysis
  • Advanced machine learning and statistics
  • M-level modules in mathematics

Assessment method

Assessment methods include essays, closed book tests, exercises in problem solving, use of the Web for tool-based analysis and investigation, mini-projects, extended essays on specialized topics, and individual and group presentations.

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