The Master of Data Science (Health) at Durham University equips you with the analytical and computational skills to tackle complex health challenges preparing you for careers in public health, clinical research, health informatics, and digital health innovation.
Tackle real-world health challenges with data-driven insight. This conversion course equips you with the analytical and technical skills to interpret complex health data, from clinical research to public health. Learn to apply cutting-edge tools and methods that are transforming healthcare, policy, and patient outcomes.
From personalised medicine, to smart cities and sustainable solutions, data science is building a better world. At the same time, developments in technology have made the field of data science more accessible than ever, creating new opportunities to gain insight into the interactions between people and their environment – nowhere is this more true that in the health sector where the effective use of data is playing a vital role in tailored care for individuals and in improving health outcomes for the public as a whole.
Drawing on this, we have created the Master of Data Science (Health), a conversion course that opens up a future in data science even if your first degree is in a non-quantitative subject. You will learn from practicing researchers who are making a difference across a range of industries. Shared core modules across the suite of MDS courses will equip you with general data science skills and an understanding of how to apply those skills effectively, while subject-specific modules focus on the complex data and specialist methods used in the health system. It is equally suitable whether you are planning to use quantitative analysis in a research capacity, or if you are a health or social care graduate who wants to develop transferable data and modelling analysis skills for the workplace.
The course culminates in the research project, an in-depth investigation into an area of interest in which you apply the skills you’ve learned during the course to a specific topic or issue in health or social care.
The course begins with a range of introductory modules before progressing to more advanced contemporary techniques such as statistical analysis (in R) and computer science (in Python). You will also take modules that explore the use of data for clinical and public health decisions, relevant modelling techniques such as survival and epidemiological methods, and address questions such as governance and privacy.
Course structure
Year 1 modules
Core modules:
The Data Science Research Project
is a substantial piece of self directed research into an unfamiliar area of data science, or in your subject specialisation area with a focus on data science. The project can be practical, theoretical or both, and is designed to develop your research, analysis and report-writing skills.
Critical Perspectives in Data Science and AI
develops your understanding of the production, analysis and use of quantified data, and how to analyse these practices anthropologically utilising AI applications. You will learn to think ethically and contextually about quantified data, and how to apply this knowledge to practical problems in data science, including your own research project.
Health Informatics and Clinical Intelligence
examines the concepts and skills for generating health and medical evidence from electronic medical/health records and health system datasets. You will explore areas such as fundamentals of health informatics; public health data; electronic health/medical records; and applications of health informatics.
Models and Methods for Health Data Science
introduces the knowledge and skills for the modelling and analysis of routinely collected health data. It includes areas such as the basics of epidemiology; health economic modelling; modelling techniques for discrete data; and survival analysis.
Introduction to Statistics for Data Science
focuses on the fundamentals of statistics you will need for data science. The module covers topics such as exploratory statistics, statistical inference; linear models; classification and clustering methods; and resampling and validation.
Optional modules:
The remainder of the course will be made up of core and option modules which will vary depending on prior qualifications and experience. These have previously included:
Introduction to Computer Science
Introduction to Mathematics for Data Science
Programming for Data Science
Text Mining and Language Analytics
Data Exploration, Visualisation and Unsupervised Learning
Strategic Leadership
Machine Learning
Computational Social Science
Society, Health and Wellbeing
Ethics of Artificial Intelligence and Data Science
This interdisciplinary course is made up of modules that span across the University. It incorporates a wide range of learning and teaching methods , these include lectures, seminars, workshops and computer/practical classes. The taught elements are further reinforced through independent study, research and analysis, case studies and structured reading.
All modules are underpinned by research and embed elements of research training in both delivery and assessment. Throughout the course you will be encouraged to develop research methods, skills and ethics reflecting the methods used by the research-active staff. Overall, you will be encouraged and guided to be ‘research minded’ in all modules, and to develop these critical skills for use in future work or research.
Assessment
The Master of Data Science is assessed via a combination of essays, online assessments, reports and presentations – both individual and in small groups.
The course culminates with a major research project, which is conducted and written up as a self-directed piece of work with support from your appointed supervisor.
Entry requirements
We require a 2:1 Bachelor (Honours) degree or international equivalent in any degree subject.
Applicants with a strong data science or mathematical background may wish to consider our MSc Scientific Computing and Data Analysis programmes.
International students who do not meet direct entry requirements for this degree might have the option to complete an International Foundation Year.
Home students who do not meet our direct entry requirements, may be eligible for our Foundation Programme which offers multidisciplinary programmes to prepare you for a range of specified degree programmes.
The fees for this academic year have not been confirmed yet.
The tuition fees shown are for one complete academic year of study and are set according to the academic year of entry. Fees will be subject to an annual inflationary increase and are expected to rise throughout the programme of study. The fee listed above is for the first year of the course only.
In today’s data-driven world, the ability to capture, analyse, and communicate insights from complex information is one of the most sought-after skills by employers globally.
Graduates are equipped for exciting and meaningful careers across a wide range of sectors from science, health, and the environment to the humanities and social policy where data is driving innovation and transforming how we live and work. Whether you're influencing public health strategies, advancing climate research, or unlocking cultural insights, your data science expertise will open doors to impactful opportunities.
Department information
Natural Sciences
Our Master of Data Science programmes give you the tools to capture, analyse, and unlock insights from the vast streams of data shaping our world. These interdisciplinary degrees empower smarter decision-making across sectors from health and environment to culture and society.
The Master of Data Science programmes at Durham University equip you with the skills to capture, process, and analyse the vast and complex data shaping every aspect of modern life. From healthcare and environmental science to social policy and cultural heritage, data science is transforming how decisions are made and problems are solved.
The suite of programmes are designed as conversion degrees, ideal for students from non-data science backgrounds who want to transition into this high-impact field. You'll gain a strong foundation in data science while exploring its applications across a range of disciplines.
Choose from seven pathways tailored to your interests and career goals: the Master of Data Science or Master of Data Science with AI Applications, or specialist routes in Bioinformatics and Biological Modelling, Digital Humanities, Earth and Environment, Health, Social Analytics, and Heritage.
As a student, you’ll benefit from Durham’s interdisciplinary approach and the expertise of the Institute for Data Science, a hub for innovation that supports research and teaching across the University. Join a vibrant academic community working to transform nature, society, and culture through data.
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