- Designed for those interested in learning the underpinning theory of Data Science together with methods for implementation and application
- Explore mathematical and computational techniques for Data Science, building on your existing scientific and/or mathematical knowledge
- Study network analysis, text analysis and machine vision as well as social contexts, governance and ethical considerations
- Build upon your existing coding skills and handle complex data sets, learning multiple methods of analysis and efficient approaches to visualisation and presentation
- Undertake a project where you’ll develop skills and pursue ideas in a specific area of interest, with the support of your academic supervisor.
10th in the UK for Computer Science
The Times and The Sunday Times Good University Guide 2021
Partner to the Alan Turing Institute and home to the Institute of Data Science and Artificial Intelligence
Excellent facilities spanning a wide range of machine types and software ecosystems
Exeter's Q-Step Centre for Applied Social Data Analysis integrates the use of cutting-edge quantitative methods with the study of substantive real world issues in the social sciences
Candidates are required to have at least a 2:1 degree in a strongly numerate subject (e.g. computer science, mathematics, physics) and must be able to show evidence of good programming ability in a recognised modern computer language. Candidates may be interviewed by video conference to assess their programming ability and suitability for the course.
The Python programming language is used extensively during this course and applicants with experience in other languages will be asked to learn basic Python before commencing the course.
We may consider applications with non-standard qualifications where there is evidence of exceptional performance in modules relevant to the programme of study, significant relevant work experience, or relevant professional qualifications.
You may choose up to 30 credits of NQF Level 7 modules which are not listed above, either from within or outside the College of Engineering, Mathematics and Physical Sciences, subject to approval, timetabling and satisfaction of prerequisites.
Not all modules will be available every year, and new modules may be made available from time to time.
Part time students will follow:
You must complete at least 4 modules (60 credits) which must include ECMM443 Introduction to Data Science and ECMM444 Fundamentals of Data Science.
You must complete at least 4 modules (60 credits) one of which must be ECMM451 Data Science Research Project.
The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.
UK fees per year:
£11,500 full-time; £5,750 part-time
International fees per year:
£24,500 full-time; £12,250 part-time
We invest heavily in scholarships for talented prospective Masters students and have over £2.5 million in scholarships available, including our Global Excellence Scholarships* and Green Futures Scholarships* for international fee paying students.
For information on how you can fund your postgraduate degree at the University of Exeter, please visit our dedicated funding page.
*Selected programmes only. Please see the Terms and Conditions for each scheme for further details.
Teaching and research
Teaching is mainly delivered by lectures, workshops and online materials. Each module references core and supplementary texts, or material recommended by module deliverers, which provide in depth coverage of the subject and go beyond the lectures.
Internationally recognised research
We believe every student benefits from being taught by experts active in research and practice. All our academic staff are active in internationally-recognised scientific research across a wide range of topics. You will discuss the very latest ideas, research discoveries and new technologies, becoming actively involved in a research project yourself.
We aim to provide a supportive environment where students and staff work together in an informal and friendly atmosphere. We operate an open door policy, so it is easy to consult individual members of staff or to fix appointments with them via email. As a friendly group of staff, you will get to know us well during your time here.
The assessment strategy for each module is explicitly stated in the full module descriptions given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills. 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.
“The Sexiest Job of the 21st Century.” - Harvard Business Review
Data Science is changing the way people do business. Mountains of previously uncollectable data, generated by huge growth in online activity and appliance connectivity, is becoming available to businesses in every sector. The opportunities for businesses and individuals who can manage, manipulate and extract insights from these enormous data sets are limitless. A direct result of this is the dramatic increase in demand for individuals with the skills to turn this information into insight is outstripping supply.
Whether you’re looking to take your career in a new direction or for an MSc that will sit alongside your undergraduate degree to land you an exhilarating graduate job, you’re unlikely to find a better choice than Data Science.
Dedicated careers support
You will receive support from our dedicated Career Zone team, who provide excellent career guidance at all stages of career planning. The Career Zone provides one-on-one support and is home to a wealth of business and industry contacts. Additionally, they host useful training events, workshops and lectures which are designed to further support you in developing your enterprise acumen. Please visit the Career Zone for additional information on their services.