MSc Health Data Science

Course overview

This MSc combines healthcare with data science, focusing on statistics, machine learning, data analysis and management. You’ll work with tools such as R, SQL and Python and apply them to real healthcare and biomedical data.

Course details

Degree level

Master's

Duration

1 year

Intake

January 2027

Tuition fee

£22,950 / year

Initial deposit

50% of the first-year tuition fee after scholarship deductions, after Credibility Interview.

Country

Wales

Campus

Singleton Park Campus

About this information

The details on this page have not yet been checked against the official course page by our team. Fees, intakes and requirements can change, so always confirm them on the official course page before you apply.

Not recorded here yet: Pakistan-specific requirements.

English Language Requirements

Main English Requirements

Only the tests listed here are shown as accepted for this course.

Entry requirements

General entry requirements

• Academic: 2:2 degree or equivalent in a quantitative subject such as Mathematics, Statistics, Computing, Engineering, Physics or Biomedical Science. • Your degree should include significant statistics/computing or health-data/medical content. • Relevant health data science experience may also be considered. • IELTS: 6.5 overall, minimum 6.0 in each component

Scholarships & discounts

Undergraduate – Thrive Bursary • £4,000 reduction in tuition fees for the first year • £2,000 progression bursary in subsequent years, applied as a tuition fee discount Postgraduate – International Excellence Scholarship • £5,000 tuition fee discount • A separate application is required to apply for the scholarship. (link will be shared soon)

Pre-CAS interview

Required

Yes — a Pre-CAS / credibility interview is part of the process

Stage

Before the initial deposit is paid

Format

Credibility interview

Course modules

• Programming Skills in Health Data Science: Learn programming techniques for working with health data. • Statistics for Health Data Science: Study statistical methods used in health research. • Introductory Analysis of Linked Health Data: Learn how linked healthcare datasets are analysed. • Bioinformatics for Genome Analysis: Explore computational analysis of genetic and genomic data. • Machine Learning in Healthcare: Apply machine learning techniques to healthcare problems. • Health Data Visualisation: Learn how to analyse and present health data visually. • Health Data Dissertation: Complete an independent research project using health data.