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Undergraduate Study

BSc Data Science - 2024 entry

Please note: The below is for 2024 entries. Click here for 2025 entries.
UCAS code GG16
Duration 3 years
Entry year 2024
Campus Streatham Campus
Discipline Data Science

Web: Enquire online
Phone: +44 (0)1392 723192

Typical offer

View full entry requirements

A levels: AAA-AAB
IB: 36/666-34/665

Contextual offers

A-Level: ABB-BBB
IB: 32/655-30/555


  • This course has been developed in collaboration with industry, using current methods, platforms, software and data, to ensure you are fully prepared for the workplace upon graduation
  • You will develop fundamental mathematical and computational techniques via a mixture of individual and group learning
  • This degree will support you in becoming an outstanding, dynamic problem solver with an excellent technical skillset, preparing you for a fantastic array of professions that require the technical expertise of a data scientist
  • Taught by active researchers, this course covers the core areas of mathematics and data science while introducing you to applications and social contexts
  • Research projects in each academic year will allow you to develop independent research and project management skills in an area of interest, using real world datasets and guided by an academic supervisor

View 2025 Entry

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How to apply


Web: Enquire online

Phone: +44 (0)1392 72 72 72

Top 20 for Computer Science

20th in The Times and The Sunday Times Good University Guide 2024

Partner to the Alan Turing Institute

Home to Exeter's Institute for Data Science and Artificial Intelligence

Top 20 in the UK for graduate prospects

16th for graduate prospects for Computer Science in the Complete University Guide 2024 (94%)

Entry requirements (typical offer)

Qualification Typical offer Required subjects
A-Level AAA-AAB GCE AL Maths grade B in Mathematics, Pure Mathematics or Further Mathematics
IB 36/666-34/665 HL 6 in Mathematics (Analysis and approaches or Applications and interpretations)
BTEC DDD Applicants studying a BTEC Extended Diploma will also require GCE AL Maths grade B
GCSE 4/C Grade 4/C in GCSE English Language
Access to HE 30 L3 credits at Distinction Grade and 15 L3 credits at Merit Grade 12 L3 credits at Merit Grade in an acceptable Mathematics subject area
T-Level T-Levels not accepted N/A
Contextual Offer

A-Level: ABB-BBB
IB: 32/655-30/555

Specific subject requirements must still be achieved where stated above. Find out more about contextual offers.

Other accepted qualifications

View other accepted qualifications

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 B1. Please visit our English language requirements page to view the required test scores and equivalencies from your country.

NB General Studies is not included in any offer.

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

International Foundation programmes

Preparation for entry to Year 1 of an undergraduate degree:

Course content

The BSc Data Science is an innovative interdisciplinary course designed with industry and aimed at those wishing to work or research in the data science sector. The course will cover the core areas of mathematics and computer science. It also includes new modules which will introduce you to applied data science as well as social context. Research projects in each academic year will allow you to develop research and project management skills in an area of interest, using real world datasets, guided by a leading academic supervisor.

Please note: This programme is currently in development. The modules listed below are indicative of the topic areas you can expect to cover on the course, but are subject to change.

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.

In your first year, you will be introduced to the fundamental technical and professional skills needed to successfully engage with machine learning, artificial intelligence and data science. You will gain core knowledge and practical skills relating to data structures and algorithms and will practice the techniques and applications of AI and machine learning.

Compulsory modules

ECM1410Object-Oriented Programming15
COM1011Fundamentals of Machine Learning15
ECM1407Social and Professional Issues of the Information Age15
ECM1413Computers and the Internet15
ECM1414Data Structures and Algorithms15
ECM1415Discrete Mathematics for Computer Science15
ECM1416Computational Mathematics15

In year 2 you will gain theoretical and practical understanding of some of the more advanced techniques in machine learning and data science. You will also learn how methods are applied to workflows linked to tackling challenges in real-world social issues. Through lectures and practical exercises, you will develop vital professional and interpersonal skills needed to work effectively in the mathematical and digital sector, including project management and teamwork.

Compulsory modules

ECM2414Software Development15
ECM2419Database Theory and Design15
MTH2006Statistical Modelling and Inference30
COM2011Machine Learning and Data Science15

Optional modules

ECM2434Group Software Engineering Project15
Select 30 credits from:
COM2014Computational Intelligence15
*Free choice elective15

Year 3 will comprise group and individual work as you carry out your final year project. Optional modules will give you the opportunity to specialise in areas that are most suited to your interests, giving you a strong foothold for future career development.

Compulsory modules

COM3021Data Science at Scale15
COM3022Data Science Individual Project 130
COM3023Machine Learning and AI15

Optional modules

Select up to 45 credits:
ECM3408Enterprise Computing15
ECM3412Nature Inspired Computation15
ECM3422Computability and Complexity 15
ECM3423Computer Graphics15
ECM3428Algorithms that Changed the World15
ECM3446High Performance Computing 15
MTH3019Mathematics: History and Culture15
MTH3024Stochastic Processes15
MTH3028Statistical Inference: Theory and Practice15
MTH3041Bayesian statistics, Philosophy and Practice15
MTH3044Bayesian Data Modelling15
You may select up to 30 credits of other options:
EMP3001Commercial and Industrial Experience15
*Free choice elective - up to 30 credits30

I chose Data Science because I didn’t want to just focus on coding. Exeter is one of the only universities with a course that lets me combine my interests and passion in all areas, such as statistics and machine learning.

Already during my first two months I’ve touched upon mathematics and the basics of programming. It’s really exciting and will open doors to a huge range of careers.

Read more from Natalie


Studying BSc Mathematics and Data Science at the University of Exeter


Tuition fees for 2024 entry

UK students: £9,250 per year
International students: £27,000 per year


The University of Exeter has many different scholarships available to support your education, including £5 million in scholarships for international students, such as our Global Excellence Scholarships*. Financial support is also available 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.

Find out more about tuition fees and scholarships

Learning and teaching

Lectures, seminars and workshops

We make use of a variety of teaching styles, including lectures, seminars, workshops and tutorials. Most modules involve two or three lectures per week, so you would typically have about 10 lectures each week. In addition, workshops and tutorials support and develop what you’ve learnt in lectures and enable you to discuss the lecture material and coursework in more detail. You’ll have over 15 hours of direct contact time per week with your tutors and you will be expected to supplement your lectures with independent study. You should expect your total workload to average about 40 hours per week during term time.

Virtual learning environment

We’re actively engaged in introducing new methods of learning and teaching, including increasing use of interactive computer-based approaches to learning through our virtual learning environment, where the details of all modules are stored in an easily navigable website. You can access detailed information about modules and learning outcomes and interact through activities such as the discussion forums.

A research and practice led culture

We believe every student benefits from being taught by experts active in research and practice. You will discuss the very latest ideas, research discoveries and new technologies in seminars and in the field and you will become actively involved in a research project yourself. All our academic staff are active in internationally-recognised scientific research across a wide range of topics. You will also be taught by leading industry practitioners.


Modules are assessed by a combination of continuous assessment through small practical exercises, project work, essay writing, presentations and exam.

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
  • Data Science
  • Entrepreneurship
  • Law
  • Leadership
  • Social Data Science

Find out more about proficiency options

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Your future

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.

This 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.

Industrial Experience

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.

Career Paths

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
  • Analyst
  • Business Statistician
  • Data Analyst
  • Data Architect
  • Data Scientist
  • Machine Learning
  • Engineer
  • Quantitative Researcher
  • Research Analyst
  • Research Scientist

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