| UCAS code | 1234 |
|---|---|
| Duration | 1 year full time 2 years part time |
| Entry year | 2025 |
| Campus | Streatham Campus |
| Discipline | Data Science and Analytics |
| Contact | Web: Enquire online |
| Typical offer | Applicants are required to have either a 2:1 in a non-related science undergraduate degree, OR a 2:1 in any other degree subject and A Level Mathematics at Grade A, or equivalent. |
|---|---|
Overview
- MSc Data Science is the programme for you if you want to explore the role of data science in a range of sectors.
- Nearly every sector requires data science expertise – from healthcare, wellbeing and retail to environment, banking, finance and government agencies.
- This conversion programme teaches graduates from a non-computing background* the necessary skills to understand the theory of data science and apply it to their area of interest.
- By choosing optional modules and a research project that match your interests, you can curate a masters in data science that meets your career goals.
- Your research project, which is supervised by an expert data scientist, brings together your learning and enables you to apply it to a practical or theoretical problem.
- You will have access to our latest computer facilities which are world-class spacious teaching labs allowing comfortable, collaborative working in a sensory-friendly environment.
*If you have a computing background, we very strongly advise that you apply for one of our advanced programmes, please see MSc Advanced Computer Science or MSc Advanced Computer Science with Business.
Fast Track (current Exeter students)
Data Science at the University of Exeter equips students with technical skills to understand, manage and store large data sets, together with the flexibility to apply powerful analytics to data across industry, business and research.
Top 10 in the UK for graduate prospects
Joint 9th for graduate prospects for Computer Science in the Complete University Guide 2025 (94%)
£50 million investment in our Data Science and Artificial Intelligence capabilities
Excellent facilities spanning a wide range of machine types and software ecosystems and access to world-class computer labs
Long-established partnership with the Alan Turing Institute and home to the Institute of Data Science and Artificial Intelligence
Top 10 in the UK for graduate prospects
Joint 9th for graduate prospects for Computer Science in the Complete University Guide 2025 (94%)
£50 million investment in our Data Science and Artificial Intelligence capabilities
Excellent facilities spanning a wide range of machine types and software ecosystems and access to world-class computer labs
Long-established partnership with the Alan Turing Institute and home to the Institute of Data Science and Artificial Intelligence
Entry requirements
Applicants are required to have at least a 2:1 degree in a non-related science undergraduate degree, or a 2:1 in any other degree subject and A Level Mathematics at Grade A or equivalent.
Please note, this is a conversion course designed to allow students from a wide range of backgrounds to pursue a career in data science. If you have studied Computer Science, Mathematics, Physics, Engineering or other related degree, we very strongly advise that you apply for one of our advanced programmes, please see MSc Advanced Computer Science or MSc Advanced Computer Science with Business. The MSc Data Science programme is a conversion course intended for students who have a non-related degree background therefore the course content has been designed so that it is appropriate for that entry level.
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.
Entry requirements for international students
Please visit our entry requirements section for equivalencies from your country and further information on English language requirements.
Entry requirements for international students
English language requirements
International students need to show they have the required level of English language to study this course. The required test scores for this course fall under Profile B3. Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
The MSc Data Science programme is designed for individuals from diverse academic non-computing backgrounds to learn the underpinning theory of data science together with methods for implementation and application. The programme has compulsory modules to ensure you learn a comprehensive set of data science skills alongside a choice of optional modules, enabling you to flex the programme to meet your interests and aspirations.
You have the option to study this programme full-time over one year or part-time over two years.
Full time programme structure
- Term 1: You will complete the compulsory modules COMM108 Data Systems, COMM109 Programme with Python, ECMM443 Introduction to Data Science, and ECMM445 Learning from Data.
- Term 2: In addition to the compulsory modules ECMM422 Machine Learning and SOCM033 Data Governance and Ethics, you will complete 30 credits of optional modules from the list below. The taught element of your course will be completed by May and you will have until September to complete your research project (COMM514).
Part time programme structure
- Year 1: You must will complete at least 4 modules (60 credits) which must include ECMM443 Introduction to Data Science and COMM109 Programme with Python.
- Year 2: You must complete at least 4 modules (60 credits) and the compulsory COMM514 Research Project (60 credits).
All students (full or part-time) may choose up to 30 credits of NQF Level 7 modules which are not listed in the optional modules list below, either from within or outside the Faculty of Environment, Science and Economy, 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.
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.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| COMM514 | Research Project | 60 |
| ECMM443 | Introduction to Data Science | 15 |
| ECMM445 | Learning from Data | 15 |
| COMM108 | Data Systems | 15 |
| COMM109 | Programme with Python | 15 |
| ECMM422 | Machine Learning | 15 |
| SOCM033 | Data Governance and Ethics | 15 |
Optional modules
| Code | Module | Credits |
|---|---|---|
| Select 30 credits | ||
| ECMM426 | Computer Vision | 15 |
| ECMM447 | Social Networks and Text Analysis | 15 |
| ECMM450 | Stochastic Processes | 15 |
| MTHM508 | Bayesian Philosophy and Methods in Data Science | 15 |
| BEMM190 | Digital Transformation | 15 |
Fees
2025/26 entry
UK fees per year:
£14,300 full-time; £7,150 part-time
International fees per year:
£30,300 full-time; £15,150 part-time
Scholarships
The University of Exeter has many different scholarships available to support your education, including £5 million in scholarships for international students applying to study with us in the 2025/26 academic year, such as our Exeter Excellence Scholarships*.
For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
*Terms and conditions apply. See online for details.
Academic partners
Our long-established partnership with the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, means that we have strong connections to the UK AI research community. Currently we host 11 Turing Fellows and one Turing AI Fellow at the University. Turing Fellows are established scholars with proven research excellence in data science, AI, or a related field. Lectures, conferences and seminars organised by Turing and the Turing University Network are usually open to our students to attend either in person or online.
Teaching and research
All our courses are taught by active researchers who work closely with industrial partners. Our module leads are renowned in their field with prestigious fellowships and awards, many also consulting with major companies. Teaching is mainly delivered by lectures, workshops and online materials. You will have access to comprehensive online learning materials through the University’s virtual learning environment, including recorded lectures. 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. Find out about our data science researchers by discovering our hub for data-intensive science and artificial intelligence at the Institute for Data Science and Artificial Intelligence (IDSAI). You can also read more about our current computer science research.
Investment in data science and artificial intelligence
The University has invested £50 million in the development of its Data Science and Artificial Intelligence capabilities. The Accelerating Data Science and Artificial Intelligence (ADA) project has been running since 2023 and has invested in teaching, research and infrastructure which this programme benefits from.
Supportive environment
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.
Assessments
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 specialised topics, and individual and group presentations.
Careers
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.
Graduate destinations
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. Examples of graduate roles include data scientist, machine learning scientist, Python programmer and software engineer.
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.
