Health Data Analytics MSc/PG Dip/PG Cert

Students on the Health Data Analytics programme will learn about mathematical and statistical approaches to understanding health data, including operational research, machine learning and health economics. They will learn the fundamentals of how health data is collected, represented, stored and processed as well as how to analyse it effectively and how best to present analyses to have an impact on decisions.

Students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), five optional modules (75 credits) and a research project (60 credits).

A Postgraduate Diploma (120 credits, flexible study 2-5 years) is offered.

A Postgraduate Certificate (60 credits, flexible study over a period of two years) is offered.

• Principles of Health Data Analytics
• Research Methods in Healthcare
• Statistical Methods for Health Data Analytics

Students choose five of the following:

• Key Principles of Health Economics
• Public Health Data Science
• Learning Health Systems
• Information Law & Governance in Clinical Practice
• Economic Evaluation of Health Care
• Essentials of Informatics for Healthcare Systems
• Machine Learning in Health Care
• Clinical Decision Support Systems
• Patient Safety and Clinical Risk

Please note that the optional modules listed here may be subject to change.

All MSc students undertake an independent research project, normally based at their place of work, which culminates in a piece of work written in the style of a journal article.

The programme is taught by 'blended learning', and therefore includes interactive online teaching and face-to-face lectures, seminars and workshops including substantial use of examples of real clinical systems. Assessment is through examination, critical evaluations, technical tasks, coursework and project reports, compulsory programming and database assignments, and the dissertation.