Health Data Science (Taught)

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 models of healthcare delivery worldwife are 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 and the advent of AI, 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

• Introduction to Statistics

• Statistical Modelling and Inference in Health.

The second semester offers 11 optional units, of which four need to be completed (for those studying for a MSc).

The optional units include:

• Design and Analysis of Randomised Controlled Trials

• Tutorials in Advanced Statistics

• Introduction to Clinical Bioinformatics

• Machine Learning and Advanced Data Methods

• Mathematical Computing for Medical Imaging

• Decision Support Systems

• Digital Transformation Project

• Introduction to Health Informatics

• Principles of Digital Epidemiology

• Medical Image Analysis with Artificial Intelligence

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.