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Data Science for Research in Health and Biomedicine - MSc/PGDip/PGCert

Course Description

Students will become expert in linking and analysing large complex datasets, using techniques which are transforming medical research and creating exciting new commercial opportunities. Graduates will be equipped for roles in the pharmaceutical industry, the NHS and technology start-ups, as well as academia.

Degree information

Students learn how to design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The content is drawn from epidemiology, computer science, statistics and other fields, including genetics.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits) and a dissertation/report (60 credits). A Postgraduate Diploma (120 credits) is offered. A Postgraduate Certificate (60 credits) is offered.

Core modules
-Principles of Epidemiology Applied to Electronic Health Records Research
-Data Management for Health Research
-Statistics for Epidemiology and Public Health
-Statistical Methods in Epidemiology
-Topics in Health Data Science

Optional modules
-Advanced Statistics for Records Research
-Database Systems
-Information Retrieval and Data Mining
-Principles of Health Informatics
-Machine Learning in Healthcare and Biomedicine
-Statistics for Interpreting Genetic Data

All students undertake an independent research project which culminates in a dissertation.

Teaching and learning
The programme is delivered by clinicians, statisticians and computer scientists from UCL, including leading figures in data science. We use a combination of lectures, practical classes and seminars. A mixture of assessment methods is used including examinations and coursework.


Students on this programme will be passionate about research and know that, in the 21st century, some of the most exciting, stimulating and productive research is carried out using large collections of data acquired in big collaborative endeavours or major public or private initiatives. Graduates will build on that passion and the experience gained on the programme and develop careers as entrepreneurs, scientists and managers, working in industry, academia and healthcare.

The programme is designed to meet a need, identified by the funders of health research and by a number of industrial organisations and healthcare agencies, for training in the creation, management and analysis of large datasets. This programme is practical, cross-disciplinary and closely linked to cutting-edge research and practice at UCL and UCL’s partner organisations. Data science is arguably the most rapidly growing field of employment at the moment and employers recruiting in health data science include government agencies, technology companies, consulting and research firms as well as scientific organisations. A number of employers are supporting the programme in different ways, including providing paid internships to selected students.

Why study this degree at UCL?

The staff delivering the teaching are international experts in health data science and students will learn about cutting-edge research projects.

The collaboration is part of the Farr Institute, a network of centres of excellence created to enhance the UK’s strength in data-intensive research. This MSc will draw on that collaboration, giving students access to the most advanced research in the field.

Visit the Data Science for Research in Health and Biomedicine - MSc/PGDip/PGCert page on the University College London website for more details!

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Student Profiles

Entry Requirements

A minimum of an upper second-class Bachelor's degree, or equivalent, in a clinical or a scientific discipline with a significant computational or mathematical element.

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Recipient: University College London

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