Health Data Science

Our MSc Health Data Science course aims to create a new breed of scientist who can understand the healthcare sector and medicine, how data is collected and analysed, and how this can be communicated to influence various stakeholders.

The current model of healthcare delivery in the UK is subject to unprecedented challenges. An ageing population, the impact of lifestyle factors and increasing costs mean that the existing approaches may become unsustainable.

This, coupled with a drive towards personalised medicine, presents an opportunity for a step change in healthcare delivery.

To do this, we need to make best use of the health data we collect and create a better understanding of the relationship between treatments, outcomes and patients.

This MSc promotes the need for translational thinking to provide the knowledge, skills and understanding that will be applied across new challenges within healthcare delivery.

A multidisciplinary approach to health data science is the focus of this course, including students from a variety of professional backgrounds. The structure of the MSc ensures that you will share knowledge with each other and learn to work in multidisciplinary teams, rather than in specialist silos.

You will be taught by world-leading professionals and academics in the field of health data science, statistics, machine learning, information engineering, omics and digital biology, and digital transformation of the healthcare system.You will also mix with students from a range of disciplines from all over the world.

The current structure of the course (subject to change) involves four mandatory units in the first semester including:

- Introduction to Health Data Science

- Programming for Health Data

- Fundamentals of Mathematics and Statistics

- Statistical Modelling and Inference in Health.

The second semester offers ten optional units, of which four need to be completed (for those studying for a MSc).

The optional units include:

- Statistics for Randomised Trials

- Tutorials in Advanced Statistics

- Principles of Digital Biology

- Healthcare Multi-Omics

- Machine Learning and Advanced Data Methods

- Computational Imaging (including machine learning techniques)

- Clinical Decision Support

- Digital Transformation

- Introduction to Health Informatics

- Digital Epidemology

There is also a 60-credit research project, which involves writing a dissertation.

PhD with integrated master's

If you're planning to undertake a PhD after your master's, our Integrated PhD programme will enable you to combine your postgraduate taught course with a related PhD project in biology, medicine or health.

You can also visit this page for examples of projects related to integrated master's courses.