| UCAS code | GG18 |
|---|---|
| Duration | 3 years |
| Entry year | 2025 |
| Campus | Streatham Campus |
| Discipline | Mathematics |
| Contact | Web: Enquire online |
| Typical offer | A levels: AAA-AAB |
|---|---|
|
A-Level: ABB-ABC |
Overview
- An interdisciplinary degree designed in partnership with industry and combining traditional mathematical techniques with exciting contemporary applications in the field of data science
- Allows you to use mathematics to develop a deeper understanding of the processes behind data manipulation
- Become expert at handling large and complex datasets and understand the statistical considerations which can affect results, such as bias and uncertainty
- Study topics such as machine learning, artificial intelligence, statistical modelling and programming
- Research projects in each academic year will allow you to develop project management skills in your area of interest, using real world datasets and guided by an academic supervisor
Discover Mathematics at the University of Exeter.
Top 20 in the UK for Mathematics
16th in The Times and The Sunday Times Good University Guide 2024
16th for Mathematics in the Complete University Guide 2024
Study abroad at one of our partner universities in Europe, USA, Canada, Australia and China
Partner to the Alan Turing Institute and home to Exeter’s Institute of Data Science and Artificial Intelligence
Entry requirements (typical offer)
| Qualification | Typical offer | Required subjects |
|---|---|---|
| A-Level | AAA-AAB | GCE AL Maths grade A Candidates may offer GCE AL Maths, Pure Maths or Further Maths. |
| IB | 36/666-34/665 | HL6 in Mathematics (Analysis and Approaches) |
| BTEC | DDD | Applicants studying a BTEC Extended Diploma are also required to achieve grade A at A' Level in Mathematics, Pure Mathematics or Further Mathematics. |
| GCSE | 4 or C | Grade 4/C in GCSE English language |
| Access to HE | 30 L3 credits at Distinction Grade and 15 L3 credits at Merit Grade | 15 L3 credits at Distinction Grade in an acceptable Mathematics subject area |
| T-Level | T-Levels not accepted | N/A |
| Contextual Offer | A-Level: ABB-ABC |
Specific subject requirements must still be achieved where stated above. Find out more about contextual offers. |
| 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 B2. 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 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.
First year modules introduce you to the fundamental technical and professional skills needed to understand and engage with machine learning, artificial intelligence and data science. You will learn core knowledge and practical skills relating to data structures and algorithms that are commonly applied in this topic area.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| ECM1400 | Programming | 15 |
| ECM1410 | Object-Oriented Programming | 15 |
| MTH1002 | Mathematical Methods | 30 |
| MTH1004 | Probability, Statistics and Data | 30 |
| COM1011 | Fundamentals of Machine Learning | 15 |
| ECM1407 | Social and Professional Issues of the Information Age | 15 |
| MTH1000 | Foundations | 0 |
Second year compulsory modules further develop your knowledge of computational intelligence, data science in society and software development, giving you a broader skill set to continue on to your final year.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| MTH2003 | Differential Equations | 15 |
| MTH2004 | Vector Calculus and Applications | 15 |
| MTH2006 | Statistical Modelling and Inference | 30 |
| COM2011 | Machine Learning and Data Science | 15 |
| ECM2434 | Group Software Engineering Project | 15 |
Optional modules
| Code | Module | Credits |
|---|---|---|
| Select 30 credits from: | ||
| COM2014 | Computational Intelligence | 15 |
| * | Free choice elective | 15 |
In your final year you’ll choose from advanced modules in a wide range of topics. Industry-linked projects also take place and work placement opportunities are recommended. This variety of learning gives you practical experience and the confidence to conduct individual research, applying your expertise to solve real mathematical problems and find computing solutions.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| COM3021 | Data Science at Scale | 15 |
| COM3022 | Data Science Individual Project 1 | 30 |
| COM3023 | Machine Learning and AI | 15 |
Optional modules
| Code | Module | Credits |
|---|---|---|
| Select three modules (45 credits) at level 6, to include at least 2 of the following: | ||
| MTH3001 | Theory of Weather and Climate | 15 |
| MTH3006 | Mathematical Biology and Ecology | 15 |
| MTH3007 | Fluid Dynamics | 15 |
| MTH3008 | Partial Differential Equations | 15 |
| MTH3019 | Mathematics: History and Culture | 15 |
| MTH3022 | Graphs, Networks and Algorithms | 15 |
| MTH3024 | Stochastic Processes | 15 |
| MTH3028 | Statistical Inference: Theory and Practice | 15 |
| MTH3030 | Mathematics of Climate Change | 15 |
| MTH3041 | Bayesian statistics, Philosophy and Practice | 15 |
| MTH3042 | Integral Equations | 15 |
| MTH3044 | Bayesian Data Modelling | 15 |
| MTH3045 | Statistical Computing | 15 |
| MTH2XXX/3XXX | Any other level 2 or 3 Mathematics module | 15 |
Accreditations
Accredited by the Institute of Mathematics and its Applications (IMA) (IMA) for the purpose of meeting in part the educational requirement for chartered status. This programme will meet the educational requirements of the Chartered Mathematician designation, awarded by the Institute of Mathematics and its Applications, when it is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency (QAA) for taught masters degrees.
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.
Natalie
Studying BSc Mathematics and Data Science at the University of Exeter
Fees
Tuition fees for 2024 entry
UK students: £9,250 per year
International students: £27,000 per year
Scholarships
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.
Learning and teaching
All our degrees involve a combination of teaching methods, including lectures, seminars, examples classes, workshops and tutorials. Most modules in mathematics involve three one-hour lectures per week, so you typically have 12 lectures per week. In the first year there are tutorial classes for each module every fortnight, except for modules involving computing or project work. Thus in the first year you would typically have around 16 contact hours per week. In the first term, the ‘Foundations’ module helps you with the transition from A level to university mathematics.
Private study and support
In addition to lectures and seminars, you should spend about 20 hours per week in private study. Working through examples and solving problems is a vital part of learning mathematics, and we advise you attempt all coursework problems, whether formally assessed or not. You will be allocated a personal tutor who will be happy to advise or put you in touch with support services and you are encouraged to discuss mathematical problems or questions with tutors and lecturers who advertise regular office hours. Extra support is available, for example through lunchtime mathematics surgeries or our peer mentor scheme, and we have an active student-staff liaison committee.
Project and computer work
There are modules at all levels that involve project work and report writing, and the final year project is a major piece of research and writing that allows you to go into depth for a specific area under the guidance of a member of academic staff. You can choose from wide range of possible project topics each year, or negotiate a topic/title with a member of academic staff. Several of the modules develop skills to use a range of modern computer tools for working with data, programming or symbolic algebra as well as typesetting and presentation.
Elective modules
Once you have mastered the foundations, our mathematics programmes offer in later years a wide range of options within the programme. In addition to the named degrees with study abroad, professional experience and year in industry, you can take optional (called elective) modules from all over the university in years 2 and 3. These options are subject to your availability, having the appropriate background (pre-requisites) and certain programme constraints.
A research and practice led culture
You will benefit from teaching by academic staff comprising internationally-recognised mathematicians, scientists and practitioners active across a wide range of topics in pure and applied mathematics, statistics and applications. As you progress through your degree, you will hear about the latest mathematical research and have opportunities (for example, the independent research project) to become actively involved in a research project yourself.
Assessment
Assessment for all degrees is through a combination of examinations and coursework. Examinations are the more important part of the process, but the coursework helps you to work steadily throughout your degree. This is particularly important in Mathematics where the subject matter develops logically as the degree progresses. Written examinations for mathematics modules are held in January and May/June of the first and second years and in May/June of each subsequent year. Some modules have tests, essays, presentations and/or project reports that contribute to the assessment.
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
- Law
- Social Data Science
- Entrepreneurship
- Leadership
Your future
Your curriculum has been developed with partners, including IBM, the Met Office, South West Water, Black Swan and Oxygen House. Throughout your studies you will conduct individual and group projects using real world data sets. Modules will use current industry methods, platforms, software and data, to ensure that they are fully reflective of workplace practice.
We’ve designed our degrees with employability firmly in mind. As well as hard skills such as programming and data analysis, you’ll develop important work place skills such as communication, presentation and teamwork.
There is an established strong market demand for suitably skilled data scientists and data science skills are increasingly being sought across many sectors, particularly by the finance and accounting industries, supermarkets, online retailers such as Amazon and the NHS.
You’ll be able to meet with local and national employers who regularly visit the university to engage with students, hosting mock interviews, CV workshops, drop-ins and lectures. This is a great opportunity for you to find out more about the day to day activities of their business and recruitment opportunities. Our Careers Service also host a wealth of employer activity, such as Careers Fairs, so you’ll never be short of chances to network with potential employers.
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 Mathematics but also in wider fields. Examples of roles recent graduates are now working as include:
- Accountant
- Actuary
- Analyst Programmer
- Business Analyst
- Credit Risk Analyst
- Data Science Developer
- Investment Analyst
- Software Engineer
- Statistician
- Tax Manager
