| 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 | 2:1 Honours degree |
|---|---|
Overview
- This is a conversion programme for graduates from a non-computing background who aspire to work with data in a range of industries.
- By studying Data Science at Exeter you will be joining a rapidly growing department that is already among the top ten for computer science in the UK.
- This programme offers you the flexibility to pursue data science according to your own passions.
- Designed for those interested in learning the underpinning theory of Data Science together with methods for implementation and application.
- A large component of the degree involves a research project which is a one-to-one engagement with a mentor from the university who will be an active data scientist and leader in their field.
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.
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 cutting-edge quantitative methods with substantive, real-world social science issues
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 cutting-edge quantitative methods with substantive, real-world social science issues
Entry requirements
Applicants are required to have at least a 2:1 degree. No specific subjects are required. Applicants are also required to have A Level Mathematics at Grade A or equivalent.
This programme has been designed to allow students from a wide range of backgrounds to pursue a career in data science.
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
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
Part time students will follow:
Year 1
You must complete at least 4 modules (60 credits) which must include ECMM443 Introduction to Data Science and COMM108 Data Systems.
Year 2
You must complete at least 4 modules (60 credits) one of which must be COMM514 Research Project.
Students may choose up to 30 credits of NQF Level 7 modules which are not listed above, 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 |
Students on this MSc have the opportunity to take courses with the business school on digital business models and strategies. All of 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 – and consult with major companies.
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
We invest heavily in scholarships for talented prospective Masters students. This includes over £5 million in scholarships for international students, such as our Global Excellence Scholarships*.
For more information on scholarships, please visit our scholarships and bursaries 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.
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 specialized 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.
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.
