Health Data Science

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.

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

The English language level for this programme is: Standard.

Further information can be found on our English language requirements page.

This programme covers computational and statistical methods as applied to problems in data-intensive medical research. As part of this programme, you will gain an understanding of techniques that are transforming medical research and creating exciting new commercial opportunities.

Data science is an exciting area with a dynamic job market, including in healthcare. Our graduates have gone on to work for a range of companies, including large research organisations and small start-ups, while others are working in health care or pursuing their interests in universities.

The lecturers on this programme are international experts in health data science and you will learn about cutting-edge research projects. Programme content is aligned with the newly-founded Health Data Research UK (HDR UK), a multi-funder UK institute for health and biomedical informatics research, led by UCL in London. This MSc will draw on that collaboration, giving students access to the most advanced research in the field. We work closely with a range of employers to ensure that our graduates have the best possible preparation for a career in data science. This includes offering industry-sponsored dissertations for selected students.

We work closely with a range of employing organisations to ensure that our graduates have the best possible preparation for a career in data science. This includes offering industry-sponsored dissertations for selected students.

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.