| UCAS code | 1234 |
|---|---|
| Duration | 1 year full time |
| Entry year | January 2025 |
| Campus | Streatham Campus |
| Discipline | Mathematics |
| Contact |
| Typical offer | A good degree (normally a 2:2 or above). |
|---|---|
Overview
- This programme is co-created and co-delivered by the department of Mathematics & Statistics and the department of Computer Science. It combines perspectives from both disciplines and will give learners a unique combination of insights into modern statistical data science.
- Developed for non-specialists to gain essential knowledge, skills, and competencies to thrive in the rapidly evolving field of data science.
- Train in the technical aspects of data science and statistics, as well as ethical issues related to the use of data in contemporary society.
- The programme includes applications from a variety of sectors, including industry, medicine and healthcare, environment and climate.
- You will apply your learning to real-world problems in your dissertation preparing you for work in a commercial setting or further postgraduate study.
Top 20 in the UK for Mathematics and Computer Science
18th for Mathematics and 19th for Computer Science in the Complete University Guide 2025
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
Top 20 in the UK for Mathematics and Computer Science
18th for Mathematics and 19th for Computer Science in the Complete University Guide 2025
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
A good degree (normally a 2:2 or above).
Successful applicants will usually have at least an A-level or equivalent in Mathematics and/or have received quantitative skills training as part of their undergraduate programme or professional experience.
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 B2. Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
This programme will support individuals with a non-mathematical or computing background who aspire to transition into the field of data science. We provide a background in the necessary mathematics and statistics, as well as equipping students to use machine learning, data model and code in a variety of languages. The MSc includes applications across a wide variety of sectors and helps students to develop innovative and responsible approaches to the use of data.
You will develop advanced-level mathematical, statistical, machine learning and computing skills to enable you to draw and utilize insights from data sets to inform business decisions.
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 |
|---|---|---|
| COMM109 | Programme with Python | 15 |
| ECMM422 | Machine Learning | 15 |
| ECMM447 | Social Networks and Text Analysis | 15 |
| MTHM064 | Dissertation Project | 60 |
| MTHM501 | Working with Data | 15 |
| MTHM502 | Introduction to Data Science and Statistical Modelling | 15 |
| MTHM503 | Applications of Data Science and Statistics | 15 |
| MTHM506 | Statistical Data Modelling | 15 |
| SOCM033 | Data Governance and Ethics | 15 |
Fees
January 2025 entry
UK fees per year:
£13,700 full-time
International fees per year:
£29,100 full-time
Scholarships for January Start - If you are planning to join this course in January 2025, you may wish to consider applying for one of our Global Excellence Scholarships.
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
Artificial Intelligence at Exeter
Teaching on this degree is directly influenced by research undertaken within Exeter’s Institute for Data Science and Artificial Intelligence which provides a hub for data-intensive science and artificial intelligence activity within the University.
The institute’s vision for data science is to find new means of interrogating and understanding data and to apply cutting-edge data analytical methodologies to diverse questions. It is a truly interdisciplinary research community made up of data scientists, mathematicians, and computer specialists across many of Exeter’s research groups and departments.
Learning and Teaching
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
You will graduate with the skills and confidence to apply sophisticated data science methods in a wide variety of settings and interpret the results. This conversion course produces graduates who are not only skilled in their undergraduate discipline, but also in statistical data science, which is a potent and highly employable combination.
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.
