BSc Mathematics and Data Science
|Typical offer||AAA-AAB; IB: 36-34; BTEC: DDD|
Data Science at the University of Exeter
BSc Mathematics and Data Science is an interdisciplinary degree combining traditional mathematical techniques such as probability and statistics with contemporary applications in the field of data science.
Differing from our undergraduate degree in Data Science, the inclusion of mathematics in this programme will allow you to develop a deeper understanding for the processes behind data manipulation.
You will study areas such as machine learning as well as the mathematical and computational foundations which underpin data science. You’ll become expert at handling large and complex datasets and will understand the statistical considerations which can affect results, such as bias and uncertainty. You’ll also gain an overview of the social and governance context for data science.
In your final year you will undertake a major individual investigation which will form you final project or dissertation.
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.
This course is an innovative and interdisciplinary taught programme designed with industry and aimed at those wishing to work or research in data science. You will cover the core areas of mathematics and computer science as well as new modules which will introduce you to applied data science. Research projects in each academic year will allow you to develop 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.
First year modules introduce you to the fundamental technical and professional skills needed to successfully 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.
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.
In your third year, further knowledge allows you to choose modules that offer advanced courses in a wide range of topics. Industry-linked projects also take place and work placement opportunities are recommended. This variety of learning gives you advanced knowledge, practical work experience and the confidence to conduct individual research; applying your expertise to solve real mathematical problems and find computing solutions.
Entry requirements 2020
A level: AAA-AAB;
GCE AL Maths grade A
Candidates may offer GCE AL Maths, Pure Maths or Further Maths.
IB Maths HL6
BTEC Extended Diploma (2010 and 2016)
Applicants studying a BTEC Extended Diploma will also require GCE AL Maths grade A.
For any questions relating to entry requirements please contact the team via our online form or 01392 724061
International students should check details of our English language requirements
If your academic qualifications or English language skills do not meet our entry requirements our INTO University of Exeter centre offers a range of courses to help you reach the required language and academic standards.
International Foundation programmes
Preparation for entry to Year 1 of an undergraduate degree:
At the University of Exeter we are committed to the idea that all students who have the potential to benefit from higher education have the opportunity to do so. We believe that fair access to higher education is a fundamental enabler for social mobility, improving life opportunities and outcomes for individual students, while benefiting the economy and society as a whole.
Educational context can affect your grades, and we take this into account in order to recognise your potential. If you meet certain criteria, we may make you a lower offer than our typical entry requirements. Find out more about contextual offers.
Please read the important information about our Typical offer.
For full and up-to-date information on applying to Exeter and entry requirements, including requirements for other types of qualification, please see the Applying section.
Learning and teaching
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.
All our degrees involve a combination of teaching methods, including lectures, seminars, workshops and tutorials. Most modules in mathematics involve three one-hour lectures per week, so you would typically have 12 lectures per week. In the first year there are tutorial classes for each module every week and example classes 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 addition to this, you are expected to spend about 20 hours per week in private study. The tutorials and exercise classes enable you to discuss the lecture material and coursework problems. Further support is available at lunchtime mathematics surgeries run by postgraduate students. You are encouraged to discuss any mathematical problems or questions that may arise with the lecturer. All lecturers have advertised office hours when they are available to provide help. Working through examples and solving problems is a vital part of learning mathematics so coursework is set in each module.
Assessment for all degrees is through a combination of examinations and coursework. Examinations are the more important part of the process, but the assessed coursework will help you to work steadily throughout your degree. This is particularly important in Mathematics where the subject matter develops logically from fairly simple beginnings. 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. Most modules also have either a mid-term test or coursework contributing to the assessment.
Coursework typically contributes 20% to the assessment of all modules. In the third years several modules allow you to undertake further coursework to contribute to your overall degree classification.
You must pass your first year assessment in order to progress to the second year, but the results do not count towards your final degree classification.
This degree was designed with employability firmly in mind. 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 curriculum 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, including the soft skills (e.g. communication, presentation and teamwork skills) that have been consistently emphasised during consultations. 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.
We have engaged in extensive stakeholder consultation with large national and international companies (Met Office, BT, IBM) and smaller local SMEs who consistently advocate the need for a course which prepares graduates for data science and data analyst roles.