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Top 10 in the UK for our world-leading and internationally excellent Clinical Medicine research
Learn from world-leading experts
Dedicated careers support
Top 10 in the UK for our world-leading and internationally excellent Clinical Medicine research
Learn from world-leading experts
Dedicated careers support
"Our Masters in Health Data Science attracts a uniquely diverse cohort, bringing together students from a range of backgrounds like maths, engineering, biosciences and medicine. I came from a mathematics background and moved into healthcare, whereas our Co-Programme Director, Mike Weedon, started in biosciences and learnt a variety of data science skills later on. This programme is designed for both paths which creates a rich and collaborative online environment."
Harry Green
MSc Health Data Science Online Co-Programme Director
Course content
Modern medical science is becoming increasingly driven by interdisciplinary teams making discoveries from analysing large datasets. The University of Exeter is leading the way with world-class research, data science-driven environments in genomics, diabetes, neuroscience and health services.
This course will introduce you to Python language, focusing on the analysis of health data with machine learning and statistics techniques. Additionally, you'll build your computing skills with Linux, manage databases using SQL, and collaborate on coding projects with GitHub. You'll also explore the core concepts of evidence-based medicine and learn how to apply Operational Research to improve health services planning and reconfiguration.
Our research projects are unique - you’ll have the opportunity to carry out a research project, working real-world health data with external partners including the NHS and companies involved in health data. The projects will be completed online using resources such as UK Biobank.
Stage 1, Year 1 – 90 credits of compulsory modules
Stage 1, Year 2 – 90 credits of compulsory modules
Compulsory modules
Details of the modules currently offered may be obtained from the Faculty website.
Modules are offered on a carousel model with HPDM206Z Computational skills and Python for Health and Life Sciences taken first and HPDM210Z Data Science Research Project taken last (if taken for the MSc).
| Code | Module |
Credits |
|---|
| HPDM206Z |
Computing Skills and Python | 30 |
| HPDM207Z |
Research Design and Statistics | 30 |
| HPDM208Z |
Stratified Medicine | 30 |
| HPDM209Z |
Making a Difference with Health Data | 30 |
| HPDM210Z |
Data Science Research Project | 60 |
Dr Harry Green
Prof. Michael Weedon
Dr Robin Beaumont
Senior Research Fellow
Dr Harry Green
Harry is a lecturer in health data science. Harry comes from a background in pure mathematics, and moved towards medicine with a PhD in mathematical modelling of cardiac biophysics. He joined the medical school in 2017 and since then has been working as a data scientist focused on using genetics to further our understanding of chronic diseases: what causes them, and how to predict them. Harry has been teaching at universities since 2012, and has experience guiding students from a range of backgrounds, having taught on Engineering, Mathematics and Medical programmes.
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Prof. Michael Weedon
Mike Weedon is a professor of bioinformatics and human genetics. He has been at the University since 2001. Mike has published over 300 papers on gene discovery and casual inference across a range of disease phenotypes.
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Dr Robin Beaumont
Senior Research Fellow
Robin is a Senior Research Fellow in the Genetics of Complex Traits Group. His research focusses on understanding the genetic architecture of human traits using large population studies such as the UK Biobank and All of Us cohorts. His current work looks at developing statistical methods and analysis frameworks and pipelines for understanding the effects of rare genetic variants using large-scale whole genome sequence data.
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Entry requirements
A 2:2 with honours in a strongly numerate subject (e.g. computer science, mathematics, physics) or health/life sciences. Prior coding skills are not required.
Alternatively, we will consider applications where there is evidence of strong skills in maths, computing or engineering, but not necessarily a degree.
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.
Find out more about our English language requirements »
Pay as you study
Total fees for this programme is £15,000.
To make it easier to budget, you don’t need to pay the total fee upfront. Instead, you can pay for each module as you are about to start studying it. You can pay for the whole year if you prefer, but the minimum payment is at least the cost of the module you are taking that term.
Find out more about the funding opportunities available to you, including the UK government postgraduate loan scheme.
What opportunities does this programme lead to?
Who is this course for?
This course is suitable for anyone who is interested in pursuing a career or further study in health data science. We welcome students from computer science, maths, physics or engineering but who do not necessarily have any experience in biology or health – and students from health and life sciences that are keen and interested to expand their skillset into health-related data.
Employer-valued skills this course develops
The programme uses the Python programming language, one of the most desired computer programming languages by employers. The computing skills you develop will equip for a wide range of careers in healthcare and beyond. In a world increasingly driven by AI and big data analysis, experience with coding and machine learning will only become more and more valued by employers across the world.
Work-based learning
The majority of students do their project with an external provider – providing a chance to work in the real world with real health data. Project providers include those in the NHS, pharmaceutical industry and health data companies. Students have a wide choice of projects because we have more projects than students, a result of the outstanding reputation of the programme and the students. Students often continue working with their project providers after graduation.
Career paths (graduate destinations)
Exeter’s Masters in Health Data Science (Online) provides students with excellent careers opportunities. Students from the first two on-campus cohorts have obtained positions with employers in the NHS, including NHS Digital, the Office of National Statistics, Data science and AI companies. Find out more about our on-campus Masters in Health Data Science.
Dedicated careers support
You will receive support from our dedicated Career Zone team, who provide excellent career guidance at all stages of career planning. The Career Zone provides one-on-one support and is home to a wealth of business and industry contacts. Additionally, they host useful training events, workshops and lectures which are designed to further support you in developing your enterprise acumen. Please visit the Career Zone for additional information on their services.
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