MSc Health Data Science

Overview - Health Data Science

The amount of health data available today is vast. That information has huge potential to improve health around the world, but only if it’s properly managed, analysed, and communicated. Study MSc Health Data Science at LSHTM to combine your passion for healthcare with your technical knowledge – and help identify new ways to prevent, treat, and cure disease.

Over one year (full time) or two years (part time or split study), you’ll develop the specialist skills you need to become a successful and in-demand health data scientist. Immerse yourself in an inspiring environment where world leaders in subjects like machine learning, electronic health records and epidemiology are pushing boundaries.

What you will learn

  • Discover how mathematics, programming, statistics, epidemiology, and informatics combine in this emerging discipline
  • Build your quantitative, computational, and practical data management skills as you apply statistical and machine learning approaches to analysing health data
  • Develop the professional skills you’ll depend on in your career, such as teamwork, project management, and presentation
  • Find out how and where data are collected and what that means for their quality, accessibility, and bias
  • Study ethical, security, and governance issues around collecting, storing, and using personal information

The aims and learning outcomes are detailed in the programme specification.

LSHTM’s international portfolio of research and our Medical Research Council Units in The Gambia and Uganda provide a unique opportunity to learn about the challenges of global health and the emerging role of health data science in both high- and low-income countries.

Our data science partners can provide the setting for your own research project and give you experience of what employers are looking for. As part of their MSc our students have conducted research with healthcare consultancies, pharmaceutical companies, tech companies, SMEs, government agencies, and clinical audit providers. These include IQVIA, GSK, Pfizer, The World Food Programme, The UK Office for National Statistics. and the Royal College of Surgeons.

We’re one of only six UK institutions delivering this master’s for Health Data Research UK (the UK’s national institute for health data science). That means we have demonstrated scientific excellence and a commitment to building a health data science community.

Who is it for?

Perhaps you’re a computer science graduate thinking about moving into a health-related area. Maybe you’re a scientific medical professional needing strong data skills to get to the next stage of your career. Or you could be a medical student wanting to use this degree for intercalated study.

The course is suitable for a wide range of graduates and professionals with mathematical, programming or medical expertise. It’s ideal for anyone looking to learn and apply the skills to manage, analyse and interpret large amounts of electronic health information.

Support and partnerships

This programme is supported by Health Data Research UK – the national institute for health data science. 

The programme will be delivered with the support of a number of partners, drawn from across the health data science landscape, including international healthcare consultancies (IQVIA, Panalgo), pharmaceutical companies (GSK), multinational technology companies (Microsoft Research), governmental agencies (National Institute for Health Protection), and national clinical audit providers (Royal College of Surgeons – Clinical Effectiveness UnitIntensive Care National Audit & Research Centre and Deloitte).

These partners will help ensure that our programme fits the needs of prospective employers, both within academia and in industry. They will help us offer students on this programme hands-on experience with data arising from the whole health spectrum, from the molecular to the population.


One year full-time; part-time or split-study over two years. Ways to study explained.

Intercalating study

Find out about intercalating this programme.

Health Data Science


Watch Programme Directors Keith Tomlin and Damien Tully talk about the programme.

Farzaneh Farhoush
Farzaneh Farhoush, UK

"LSHTM provides the perfect combination of programming, statistics and epidemiology. The course is also supported by Health Data Research UK".

Why this course?
Why this course - Health Data Science

Do you want to better understand the causes of disease and identify new ways to prevent, treat and cure disease?

The increasing amounts of electronically captured and stored health related data provide enormous opportunities to achieve these goals. Making optimal use of these data requires people with wide-ranging expertise in areas including statistics, programming, informatics and epidemiology.

Health Data Science at LSHTM

LSHTM is a world leader in the use of health data for research, with expertise in the creation, linkage and analysis of a wide range of data sources, encompassing data on environmental and social factors as well as ‘omic data, both human and pathogen. In addition, LSHTM has global reach and a large international network of partnerships enabling data science collaborations worldwide.

Our electronic health records (EHR) work encompasses pharmacoepidemiology, phenotyping, vaccine effectiveness/safety, health policy assessment, and infectious disease surveillance. We have expertise in using national audits for quality improvement, and developing NHS performance indicators. Our work is underpinned by an internationally recognised group of biostatistical methodologists.

Is this the right programme for me?

Medical Statistics, Epidemiology, and Health Data Science are closely related disciplines. We offer Master's degrees in each of these disciplines. Here are some of the differences in emphasis between them:

  • MSc Health Data Science
    • explores a range of machine learning techniques
    • has a greater focus on computational data skills, including programming and tools for data management
    • has a greater focus on professional skills training (e.g. teamwork, project management, presentation skills)
  • MSc Medical Statistics
    • has a greater focus on the theoretical underpinnings of the statistical methods studied
    • explores study design, for both clinical trials and observational studies
    • includes a more in-depth exploration of certain statistical methods (e.g. models for hierarchical data)
  • MSc Epidemiology
    • has a greater focus on developing the research question
    • includes an in-depth exploration of study design, protocol development and conducting appropriate statistical analyses
    • emphasises the ability to critically appraise studies and interpret results
    • offers the opportunity to learn about concepts and techniques specific to the study of infectious diseases

    What are my career prospects as a health data scientist?

    The demand for well-trained health data scientists is high and likely to increase over time. We anticipate our graduates may pursue careers in:

    • National health services
    • The pharmaceutical industry
    • Contract research organisations
    • Governmental institutions (such as the Health Protection Agency and the World Health Organization)
    • Non-governmental organisations
    • Health-tech SMEs (small and medium-sized enterprises)
    • Academia


    Structure - MSc Health Data Science

    The below structure outlines the proposed modules for this programme. Programme and module specifications provide full details about the aims and objectives of each module, what you will study and how the module is assessed.

    Structure of the year

    Term 1 (September - December) consists of ten teaching weeks for AB1 slot modules, plus one Reading Week* in the middle of the term. Followed by the Winter break.

    Term 2 (January - March) consists of a further ten weeks of teaching for C and D slot modules, plus a Reading Week in the middle of the term. C modules are taught in five half-week blocks before Reading Week. D modules are taught in five half-week blocks after Reading Week. Followed by the Spring break.

    Term 3 (April - September) consists of the project report.

    *Reading Week is a week during term where no formal teaching takes place. It is a time for private study, preparing for assessments or attending study/computer skills workshops. There are two Reading Weeks at LSHTM: one in November and the other in February.

    Term 1

    All students take five compulsory AB1 modules:

    • Thinking Like a Health Data Scientist
    • Programming
    • Health Data Management
    • Concepts and Methods in Epidemiology
    • Statistics for Health Data Science
    Term 2

    Students take a total of four study modules, one from each timetable slot (C1, C2, D1, D2).

    C1 slot

    • Machine Learning (compulsory)

    C2 slot

    • Data Challenge (compulsory)

    D1 slot

    • Analysis of Hierarchical and Other Dependent Data
    • Genomics Health Data
    • Modelling & the Dynamics of Infectious Diseases
    • Spatial Epidemiology in Public Health

    D2 slot

    • Analysis of Electronic Health Record Data
    • Bayesian Analysis
    • Environmental Epidemiology
    Term 3: Project report

    Students will start working on their summer project mid-April for submission by early September. The project will typically involve identifying appropriate data to tackle a particular research question, extracting and cleaning the data, analysing the data and creating suitable visualisations of the results. Students will describe the whole project in a detailed written report.

    Please note: Should it be the case that you are unable to travel overseas or access laboratories in order to complete your project, you will be able to complete an alternative desk-based project allowing you to obtain your qualification within the original time frame. Alternatively, you will be able to defer your project to the following year.

    Teaching methods

    As well as traditional lectures followed by problem-based practical sessions, with or without computers, teaching will include:

    • Flipped classroom approaches where students are provided with materials to read/watch independently, followed by formative assessment in class to assess understanding (e.g. via Moodle-based multiple choice questions), allowing contact time to focus on practical problem-based learning.
    • Interactive lectorials, alternating lecture-based and hands-on practical sessions.
    • Panel discussions and workshops, to stimulate debate particularly for current live controversies such as the ethics of algorithms.
    • Teamwork, particularly in the team-based module and the datathon.
    • Opportunities to develop and practice professional skills, including a range of student-led presentations, modules which require student teams to interact with a client (someone who is not a data scientist working outside of the LSHTM who wishes to “employ” our students to address a particular research question).
    Changes to the course

    Changes to the programme

    LSHTM will seek to deliver this programme in accordance with the description set out on this programme page. However, there may be situations in which it is desirable or necessary for LSHTM to make changes in course provision, either before or after registration. For further information, please see our page on changes to courses.

    Fees & Funding
    Fees - Master's Programmes
    Fees 2024/25  

    *Mobile users, scroll right to view fees

    Entry requirements
    Entry requirements - MSc intensive general

    In order to be admitted to an LSHTM master's degree programme, an applicant must:

    • hold either a first degree at Second Class Honours (2:2) standard in a relevant discipline, or a degree in medicine recognised by the UK General Medical Council (GMC) for the purposes of practising medicine in the UK, or another degree of equivalent standard awarded by an overseas institution recognised by UK ENIC or the GMC.


    • hold a professional qualification appropriate to the programme of study to be followed obtained by written examinations and judged by LSHTM to be equivalent to a Second Class Honours (2:2) degree or above.


    • have relevant professional experience or training which is judged by LSHTM to be equivalent to a Second Class Honours (2:2) degree or above.

    If you have not previously studied in the UK, you can check our guide to international equivalent qualifications for our master's degrees.

    Entry requirements - Health Data Science

    Applicants to the MSc Health Data Science are expected to have a solid foundation in mathematics. Specifically, a prior understanding of probability and statistics, calculus, linear algebra including logarithms and exponents is required. This should have been gained to undergraduate level, either as a mathematics/statistics degree or as a substantive element of other science-based undergraduate programmes. Moreover, although not a prerequisite, familiarity with programming logic and prior experience in computer programming would be beneficial. In place of a degree, significant relevant professional experience (2-3 years) in health data science or a related field involving substantial quantitative methods may be accepted.

    After submitting an application, the Programme Director will email a pre-entry assessment to evaluate the applicants quantitative and programming knowledge. This assessment must be completed to move further in the application process. The 60-90 minute online assessment will review the applicant's knowledge in probability and statistics, linear algebra, functions, calculus, combinatorics and programming/programming logic (prior exposure to writing programming syntax is essential). View the previous pre-entry assessment as an example.

    Applicants who do not meet the minimum entry requirement, but who have relevant professional experience may still be eligible for admission. Qualifications and experience will be assessed from the application.

    English requirements - Band B

    English language requirements

    If English is not your first language, you will need to meet these requirements: Band B

    It is possible to apply without English language test results however the results of a test may be listed as a condition of an offer of admission. Please see our English language requirements for more information.

    Intercalating students

    Intercalating students

    You will need the equivalent of a bachelor's degree to undertake an MSc. This will usually require you to have a BSc degree or have completed the first three years of your medical degree. More information on intercalating an MSc at LSHTM.

    Access and widening participation

    Access and widening participation

    At LSHTM we are committed to ensuring that excellent students feel encouraged to apply for a course of study with us. We have introduced an innovative contextual admissions system that is designed to support those students who have faced the greatest barriers to their learning. More information on widening participation at LSHTM.

    How to apply
    How to apply - applications

    This programme is delivered on campus.

    Applications should be made online and will only be considered once you have provided all required information and supporting documentation.

    Please also read LSHTM's Admissions policies prior to submitting your application.

    You can apply for up to two master's programmes. Make sure to list them by order of preference as consideration will be given to your top choice first.

    How to apply - deadlines and fees

    Application deadlines

    All applicants are encouraged to apply as early as possible to ensure availability of a place and a timely decision on their application. This is particularly important for applicants with sponsorship deadlines.

    We strongly advise that you apply early as popular programmes will close earlier than the stated deadline if they become full.

    The final closing dates for all taught Master’s applications for entry in the 2024/25 academic year is:

    • Sunday 21 July 2024 at 23:59 UK time for all students requiring a Student visa
    • Sunday 1 September 2024 at 23:59 UK time for all UK, Irish and non-Student visa students

    Applicants will be required to meet the conditions of their offer and provide all necessary documents by the date of their Offer of Admission.

    Application fee

    A standard non-refundable application fee of £50 applies to all taught Master’s degree programmes and is payable upon application submission. Income generated from the application fee is shared between scholarships and student hardship fund.

    Tuition fee deposit

    Applicants are required to respond to their Offer of Admission and pay the £500 deposit within 28 days of receipt, or their place will be released and the offer automatically declined. The deposit is deductible from tuition fees upon full registration with LSHTM.

    How to apply - visa

    Do you need a visa?

    Please visit our Visa & Immigration pages for advice and guidance.