Statistical Data Science

The MSc in Statistical Data Science is aimed at non-specialists, allowing students to develop the advanced-level mathematical, statistical, machine learning and computing skills to enable them to draw and utilize insights from data sets to inform decisions.  Training will be provided in the technical aspects of both Data Science and Statistics, and the societal and ethical issues related to the use of data in contemporary society. Throughout, the emphasis will be on the application of the methods that are learnt in a variety of areas including industry, medicine, healthcare, environment and climate.

The programme is co-created and co-delivered by the Department of Mathematics and Statistics and the Department of Computer Science.

The MSc in Statistical Data Science will provide training in a wide variety of data science, statistical modelling and computational techniques.  It will also cover machine learning, tools for handling large and complex datasets, image and text analysis, digital media, and the social and legal context for data analytics.  The emphasis is on learning methods and techniques through their application using real-world examples. Course content will range from introductory material covering the basic mathematical and coding techniques that will be required through to the application of cutting-edge methods for analysing complex patterns in data, and the social and legal context for data analytics. An emphasis will be placed on developing skills in self-sufficiency and autonomy.

Content will be delivered through a combination of lectures, hands-on practical sessions, individual self-study, and group work on Exeter’s Streatham campus.

The MSc Statistical Data Science is a 1-year full-time programme of study at Regulated Qualifications Framework (RQF) level 7 (as confirmed against the FHEQ).

Interim / Exit  Awards

If you do not complete the programme, you may be able to exit with a lower qualification:

Postgraduate Diploma: At least 120 credits of which 90 or more must be at level M.
Postgraduate Certificate: At least 60 credits of which 45 or more must be at level M.

Full details of assessment regulations for all taught programmes can be found in the TQA Manual, specifically in the Credit and Qualifications Framework, and the Assessment, Progression and Awarding: Taught Programmes Handbook.

Additional information, including Generic Marking Criteria, can be found in the Learning and Teaching Support Handbook. 

Personal and Academic tutoring: It is University policy that all Faculties have in place a system of academic and personal tutors. The role of academic tutors is to support you on individual modules; the role of personal tutors is to provide you with advice and support for the duration of the programme and extends to providing you with details of how to obtain support and guidance on personal difficulties such as accommodation, financial difficulties and sickness. You can also make an appointment to see individual teaching staff. Mathematics and Statistics is the ‘home’ discipline for Statistical Data Science students and each student will be allocated a Personal Tutor in Mathematics and Statistics on arrival and they can also expect reasonable access to all teaching staff for academic tutorials through appointments. In addition there is a Programme Director who will offer support and advice to all students on a programme.

Learning resources: Statistical Data Science students will use the Streatham Campus Library for access to designated books and journals and they will also be able to access additional resources for individual modules (lecture notes, quizzes, assessment feedback, etc) via the Exeter Learning Environment (ELE).

Student/Staff Liaison Committee enables students & staff to jointly participate in the management and review of the teaching and learning provision. The SSLC in Mathematics and Statistics meets termly and is chaired by a student representative.

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.

Each academic programme in the University is subject to an agreed Faculty assessment and marking strategy, underpinned by institution-wide assessment procedures.

The security of assessment and academic standards is further supported through the appointment of External Examiners for each programme. External Examiners have access to draft papers, course work and examination scripts. They are required to attend the Board of Examiners and to provide an annual report. Annual External Examiner reports are monitored at both Faculty and University level. Their responsibilities are described in the University's code of practice. See the University's TQA Manual for details.

This programme is not subject to accreditation and/or review by any professional and statutory regulatory bodies (PSRBs).