Health Data Science, MSc / PGDip / PGCert

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Health Data Science Students

Course Overview

Our MSc in Health Data Science is an interdisciplinary programme that is designed to prepare you for the constantly evolving landscape of data-driven health care.

The programme is based on a research and practice-driven approach, which enables you to engage with real health data. This approach helps you learn how to solve complex computational and analytical health-related problems that are relevant to healthcare, epidemiology and biomedical research.

The curriculum is designed to bridge disciplines and reflect the collaborative nature of health data science itself, with content covering statistical modelling, machine learning, and data analysis and management.

From early in the programme, you will work with tools and technologies used in the field, such as R, SQL and Python; developing your computational literacy alongside your knowledge of clinical, health-related data. The projects you will engage with are highly practical, and reflect real-world challenges, ranging from data handling to predictive modelling in clinical settings.

This MSc is designed to support a diverse group of graduates and professionals with backgrounds and expertise in quantitative sciences. It is particularly suitable for computer science, statistics, physics, maths or biosciences graduates, who are moving into, or looking to apply their skills in a health-related profession. It is also an ideal option for healthcare professionals interested in improving their data-related skills, to get to the next stage of their career or apply for their first job in this field.

While prior experience in statistical programming is helpful, it is not essential. You should either possess foundational knowledge or be motivated to develop these skills as part of the programme.

Why Study Health Data Science at Swansea University?

At Swansea, you will benefit from having access to:

  • World-leading research and facilities in health data
  • Relevant and transferable technical skills and software training, thoroughly preparing you for working with, and manipulating, health data
  • In-depth insight into how to use and apply advanced statistical and machine learning methods to real-world data
  • Teaching that prepares you to be able to analyse and interpret health-related data, and utilising it to help solve healthcare challenges
  • A flexible programme that can be studied either full-time or part-time, over 1 or 2 years
  • Supervision from one of our many leading experts in health data research, who will guide you through your dissertation project

Your Health Data Science experience

Your experience will be enhanced by access to our state-of-the-art facilities for health data analysis, which are based within our £100million Health Data Science Building, a world-class centre in eHealth and administrative data research, training and development.

Health Data Science is home to our Patient and Population Health and Informatics, and Population Data Science research and projects. Activities within the department have attracted £30million of UK Government funding, making the building one of the main data linkage sites for anonymised health data in the country.

The curriculum on this programme integrates task-based applied learning and self-directed study. Compulsory themes of study cover computer programming, health data modelling, machine learning and data linkage, which are taught through a combination of lectures and hands-on practical, lab sessions. A clear focus is placed on statistical methods and programming tools used in the analysis of health-related data.

Modules are taught in blocks. Most involve one or two full-day sessions per week, while one module in teaching block one is delivered during a single intensive week.  

Health Data Science employment opportunities

Graduates of this MSc pursue a range of diverse careers in healthcare analytics, public health, research and industry. Many secure roles within the NHS, health data organisations, or with government bodies entering positions as data analysts, research officers or informatics specialists.

Other destinations include joining healthcare companies or consultancy firms. A number of students also continue in academia or research institutions, pursuing a PhD in health data science, epidemiology or population health.

As a health data analyst, tasks in your daily role could include:

  • Data preparation, Using SQL or programming languages, Using clinical coding such as ICD-10 or SNOMED, Data modelling & analysis, Statistics, Machine learning, Epidemiology, Health economics, or Visualisation of data & reporting/publication

Examples of data that you may engage with in health data scientist roles include:

  • Data collected in primary (GP practice) and secondary care (hospitals), Health registries, Census data, Questionnaire data, Demographic data, Data from medical devices or fitness/health applications, Genomic data, Environmental data (e.g. temperature, precipitation, air pollution, pollen count), or Geographic Information Systems (GIS)

Modules

We're currently reviewing our curriculum to enhance your learning experience and embed skills that will benefit your future career. This means that some modules may be subject to change.

Entry Requirements

We consider all applicants on their own merits and welcome applications from students with a wide range of qualifications.