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Study information

Data Science (Professional) (Higher Apprenticeship) (2023)

1. Programme Title:

Data Science (Professional) (Higher Apprenticeship)

NQF Level:


2. Description of the Programme (as in the Business Approval Form)

The MSc Data Science (Professional) is a taught programme targeted at professionals who want to study alongside employment and are completing, or have completed, the Non-Integrated Higher Apprenticeship PGDip Data Science (Professional) programme. 120 credits from the PGDip programme will be accredited towards the MSc Data Science (Professional) using the University’s regulations governing Accreditation of Prior Learning which requires 180 credits in total for the MSc award. 
You will undertake one substantial research project worth 60 credits which will be supported by an academic with relevant expertise. You will have regular supervision meetings and complete the required submissions. You will apply the trained knowledge and skills from the previous years and do independent research to complete the project. 
Data science is a growth area with excellent career development potential. During this programme, you will develop key data science skills and learn from leading academics to gain a respected qualification while in employment. Employers of students participating in the programme will gain valuable knowledge and improve the skills base within their organisation, without losing productivity. The University of Exeter is a world-class research active institution which regularly features in UK Top-10 and Global Top-150 rankings and is making significant new investment in data science research and education.

3. Educational Aims of the Programme

The MSc Data Science (Professional) learning outcomes include; the application of research-led techniques in data science, understanding of the fundamental mathematical and computational techniques underpinning data science applications, with extensive coverage of machine learning and statistical modelling, practical skills with tools for handling large and complex datasets, understanding of image and text analysis, digital media, and the social and understanding of the legal context for data analytics. 
This programme will be taught from the Streatham campus of the University of Exeter virtually. This programme format is currently unique in the UK and represents a distinctive industry-focused approach to postgraduate training in data science.


4. Programme Structure

The MSc Data Science (Professional) programme is a one-year programme of study at Regulated Qualifications Framework (RQF) Level 7 assuming completion of the two-year PGDip and 120 credits from recognition of prior learning. The MSc award comprises a single additional stage.

5. Programme Modules

The following tables describe the programme and constituent modules. Constituent modules may be updated, deleted or replaced as a consequence of the annual programme review of this programme.  Details of the modules currently offered may be obtained from the College web site:


Stage 1

Code Title Credits Compulsory NonCondonable
COMM424DAIndividual Research Project60YesYes

6. Programme Outcomes Linked to Teaching, Learning & Assessment Methods

On successfully completing the programme you will be able to: Intended Learning Outcomes (ILOs) will be accommodated & facilitated by the following learning & teaching and evidenced by the following assessment methods:

A Specialised Subject Skills & Knowledge

1) Demonstrate enhanced knowledge of and use methods for machine learning to find patterns and relationships in complex datasets.
2) Demonstrate enhanced knowledge of and use methods for statistical modelling.
3) Describe in detail the social context of data science, including key aspects of data governance, legal requirements, and ethical considerations.
4) Explain in detail the organisational context of data science, including the role and applications of data science to business practices.
5) Apply independently computational methods for analysis of large and complex datasets, including network analysis, and image and text analysis.

Learning & Teaching Activities

The learning and teaching activities include individual literature study, data analysis, supervision and discussion, and coding exercise.

Assessment Methods

Assessment methods will include essays, project work, and individual presentations.

B Academic Discipline Core Skills & Knowledge

6) Critically analyse and interpret relevant academic and technical literature.
7) Demonstrate competence in underpinning mathematical and computational techniques, including linear algebra, probability, programming and programming tools.
8) Effectively handle large and complex datasets and prepare them for analysis.
9) Use appropriate methods for data visualisation and presentation of data.
10) Construct data analysis pipelines to test hypotheses or deliver particular goals.
11) Use appropriate statistical and machine learning methods to find patterns in complex datasets.
12) Appreciate the basic legal and regulatory requirements for data privacy, ethical use of data, and data governance.

Learning & Teaching Activities

The learning and teaching activities include individual literature study, data analysis, supervision and discussion, and coding exercise.

Assessment Methods

Assessment methods will include essays, project work, and individual presentations.

C Personal / Transferable / Employment Skills & Knowledge

13) Effectively communicate methods and results based on analysis of complex datasets in both written reports and oral presentations.
14) Demonstrate awareness of tools and technologies relevant to data science.
15) Design and manage a data analysis project from initiation to final report.
16) Work effectively independently or in a team.

Learning & Teaching Activities

The learning and teaching activities include individual literature study, data analysis, supervision and discussion, and coding exercise.

Assessment Methods

Assessment methods will include essays, project work, and individual presentations.

7. Programme Regulations

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.

8. College Support for Students and Students' Learning

A University-wide statement on student learning provision is included in the University’s TQA Manual.  As a student enrolled on this programme you will receive the personal and academic support of the Programme Coordinator and will have regular scheduled meetings with your Personal Tutor (also your project supervisor); you may request additional meetings as and when required. 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.
Information Technology (IT) Services provide a wide range of services throughout the Exeter campuses including open access computer rooms, some of which are available 24 hours, 7 days a week.  Help may be obtained through the Helpdesk, and most study bedrooms in halls and flats are linked to the University’s campus network.
Additionally, the College has its own dedicated IT support staff, helpdesk and computer facilities which are linked to the wider network, but which also provide access to some specialised software packages.  Email is an important channel of communication between staff and students in the College and an extensive range of web-based information (see is maintained for the use of students, including a comprehensive and annually revised student handbook.
The Harrison Learning Resource Centre is generally open during building open hours. The Centre is available for quiet study, with four separate rooms that can be booked for meetings and group work. Amongst its facilities, the Learning Resource Centre has a number of desks, four meeting rooms with large LCD screens, and free use of a photocopier. Also available are core set texts from your module reading lists, and undergraduate and MSc projects from the past two years.
Online Module study resources provide materials for modules that you are registered for, in addition to some useful subject and IT resources. Generic study support resources, library and research skills, past exam papers, and the ‘Academic Honesty and Plagiarism’ module are also available through the student portal (
Student/Staff Liaison Committee enables students and staff to jointly participate in the management and review of the teaching and learning provision.

10. Admission Criteria

All applications are considered individually on merit. The University is committed to an equal opportunities policy with respect to gender, age, race, sexual orientation and/or disability when dealing with applications. It is also committed to widening access to higher education to students from a diverse range of backgrounds and experience.
Entry requirements for this programme can be found on the  Postgraduate Study Page.

Candidates must satisfy the general admissions requirements, complete the pre-requisite PGDip programme, and English Language requirements of the University of Exeter.

11. Regulation of Assessment and Academic Standards

Each academic programme in the University is subject to an agreed College 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 College and University level. Their responsibilities are described in the University’s code of practice.  See the University's TQA Manual for details.

12. Indicators of Quality and Standards

Certain programmes are subject to accreditation and/or review by professional and statutory regulatory bodies (PSRBs).

14 Awarding Institution University of Exeter
15 Lead College / Teaching Institution College of Engineering, Mathematics and Physical Sciences
16 Partner College / Institution
17 Programme accredited/validated by
18 Final Award(s) MSc
19 UCAS Code (UG programmes) DSP
20 NQF Level of Final Awards(s): 7
21 Credit (CATS and ECTS) 180 credits (90 ECTS)
22 QAA Subject Benchmarking Group (UG and PGT programmes) Data Science
23 Origin Date February 8th 2023 Last Date of Revision: February 8th 2023