|Duration||4 year integrated degree programme: 1 year Foundation year plus 3 year undergraduate degree programme|
Web: Enquire online
We believe that fair access to higher education is a fundamental enabler for social mobility and are committed to delivering this through our education. We aim to widen participation and raise attainment - bridging gaps in retention, progression and success - to ensure our students enjoy the best possible outcome.
In support of the University’s Access and Participation Plan this course is only open to UK domiciled students who meet our contextual offer eligibility criteria, or are classed as Mature Students, and who may not have met the entry requirements for first-year entry or have not been able to take A-level Mathematics alongside a BTEC L3 Extended Diploma. Check if you are eligible to join this programme on our Contextual offers webpages.
- It covers the core mathematics required to successfully complete a Data Science degree programme at the University of Exeter
- You’ll be learning in a friendly and structured environment and will be supported academically and personally as you prepare to study a Data Science undergraduate degree
- Provided you achieve the specific progression criteria, you will progress into Year 1 of the BSc Data Science programme.
- Depending upon the qualifications you’ve gained prior to beginning the Foundation programme it may be possible to transfer to an undergraduate programme in Computer Science, Mathematics, Natural Sciences, Engineering or Physics which have a foundation year and provided you meet the entry requirements for that programme
- International students looking for a foundation course, please visit our INTO page.
Top 20 for Computer Science
18th in The Guardian University Guide 2023 and The Times and The Sunday Times Good University Guide 2023
Home to Exeter's Institute for Data Science and Artificial Intelligence
Partner to the Alan Turing Institute
Top 20 in the UK for graduate prospects
16th for graduate prospects for Computer Science in the Complete University Guide 2024 (94%)
We’re really proud to launch our foundation programme pathways which demonstrate our commitment to widening access to our computer science, data science, engineering, maths, physics and natural science programmes.
For any student who has not had the opportunity to demonstrate their true ability in A-level maths, whether through educational disadvantage, exceptional circumstances or making the wrong choices, this programme offers an alternative route into STEM at Exeter.
Professor Nicola King
Associate Dean for Education
|Qualification||Typical offer||Required subjects|
|A-Level||BCC||GCE AL Maths grade C. We will also accept AS Maths at A or Core Maths at A in lieu of A level Maths. Candidates may offer GCE AL Maths, Pure Maths or Further Maths.|
|IB||26/544||Maths HL 4 or SL 6|
|BTEC||DMM||BTEC Extended Diploma|
|GCSE||4/C||Grade C or 4 in GCSE English language|
|Access to HE||19 L3 credits at Distinction grade and 26 L3 credits at Merit Grade||
12 L3 credits in Maths at Pass Grade in an appropriate Mathematics subject
Grades advertised on each programme webpage are the typical level at which our offers are made and provide information on any specific subjects an applicant will need to have studied in order to be considered for a place on the programme. However, if we receive a large number of applications for the programme we may not be able to make an offer to all those who are predicted to achieve/have achieved grades which are in line with our typical offer. For more information on how applications are assessed and when decisions are released, please see: After you apply.
The Foundation Year is part of an integrated 4 year undergraduate degree programme. The information below relates to the Foundation Year only. Please see BSc Data Science for further information and details of the modules available on the degree programme you can progress to from the Foundation Year.
The course comprises of 90 credits of core maths, to elevate students’ knowledge to A-level grade A standard, plus some aspects of the further maths curriculum, but concentrating on developing core mathematical skills.
The other 30 credits comprise a project that includes key skills for university study.
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.
Exeter’s foundation has been created to support and prepare students for the challenges of an undergraduate degree in Data Science, Computer Science, Mathematics, Physics, Natural Sciences or Engineering.
The programme has been designed for students with the passion and aptitude for a degree, but who may have missed our standard entry criteria for various reasons, and is a call to widen participation and increase access to higher education.
Dr Houry Melkonian
Foundation Year Course Director
Tuition fees for 2023 entry
UK students: £9,250 per year
The University of Exeter has over £2.5 million in scholarships available for students applying to study with us in 2023 - including our Global Excellence Scholarships* for international fee paying students and financial support for students from disadvantaged backgrounds, lower income households and other under-represented groups to help them access, succeed and progress through higher education.
* Terms and conditions apply. See online for details.
Learning and teaching
The way you learn at university may be different from what you have experienced before. Depending on your course, you may encounter a variety of teaching methods.
In the Foundation year of this programme, you will experience a range of teaching and learning activities including lectures, workshops, tutorials, group projects/presentations and/or seminars. The mathematics modules at this stage comprise of 90 credits in total, while 'Science: Skills and Culture' module is 30 credits. You should expect your total workload to average about 40 hours per week during term time including guided independent study hours.
Visit our course pages for details of the Learning and Teaching methods on the BSc Data Science degree programme for the subsequent years of your chosen degree programme.
A research and practice led culture
You will benefit from teaching by academic staff comprising of internationally-recognised experts active across a wide range of topics in your chosen degree programme. As you progress through your degree, you will hear about the latest research and have opportunities (for example, the independent research project) to become involved in a research project yourself.
Private study and support
You will be allocated a personal tutor who will be happy to advise or put you in touch with support services, and we encourage you to to discuss subject related questions with tutors and lecturers who advertise regular office hours. Extra support is available, for example through our peer mentor scheme, and we have an active student-staff liaison committee.
Modules are assessed by a combination of summative assessments. You must pass your foundation year and meet the progression criteria to progress to Year 1 of the BSc Data Science programme, but the results do not count towards your degree classification.
Optional modules outside of this course
Each year, if you have optional modules available, you can take up to 30 credits in a subject outside of your course. This can increase your employability and widen your intellectual horizons.
Proficiency in a second subject
If you complete 60 credits of modules in one of the subjects below, you may have the words 'with proficiency in [e.g. Social Data Science]' added to your degree title when you graduate.
- A Foreign Language
- Social Data Science
There is an established strong market demand for suitably skilled data scientists and data science skills are increasingly being sought across the sectors, particularly by the finance and accounting industries, supermarkets, online retailers such as Amazon, and the NHS.
The BSc Data Science course has been developed with partner employers, including IBM, the Met Office, South West Water, Black Swan and Oxygen House and has been designed to deliver skills that are most valued by employers. Modules will use the employers’ methods, platforms, software and data, to ensure that they are fully reflective of workplace practice. Throughout your studies you will conduct individual and group projects using real world data sets.
This course will prepare you to be an outstanding dynamic problem solver with an excellent technical skillset. In addition to learning the core principles of Mathematics and Computer Science, you will learn soft skills that employers have told us they are looking for, such as communication and presentation skills, and the ability to work effectively in a team.
The inclusion of individual- and group-based project work in every academic year will offer you an opportunity to apply your skills to solve real world problems and prepare you for future employment.
As part of the three-year degree, you can choose to take an optional Commercial and Industrial Experience module during the vacation before the third year (subject to availability). This very rewarding opportunity allows you to gain paid work experience while earning credits towards your degree programme. Following the placement you can report on your experience which, alongside a report from the employer, enables you to count your experience as a third-year optional module. We have excellent links with employers and can provide assistance in finding suitable employment.
The broad-based skills acquired during your degree will give you an excellent grounding for a wide variety of careers, not only those related to Data Science but also in wider fields. Examples of roles recent graduates are now working as include:
- Analytics Manager
- Business Intelligence
- Business Statistician
- Data Analyst
- Data Architect
- Data Scientist
- Machine Learning
- Quantitative Researcher
- Research Analyst
- Research Scientist