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This programme, supported by Health Data Research UK (HDR UK), aims to train a new generation of world-leading health data scientists, to work in both the public and private sector. Teaching will focus on building strong quantitative, computational and practical data management skills, while providing opportunities to develop key professional skills required to be a successful health data scientist.
Health Data Science is an emerging discipline, combining mathematics, statistics, epidemiology and informatics. This programme will equip graduates with the tools and skills to manage and analyse very large diverse datasets across healthcare systems.
The programme will enable you to:
- apply statistical and machine learning approaches to analyse health-related data
- acquire the tools and skills to manage very large diverse datasets across healthcare systems
- develop the professional skills – including teamwork, project management, and presentation skills – to work as a successful data scientist in the public or private sector
- understand the varied roles of a health data scientist within the wider health and health research environment
- learn about the key sources of health data, and the context in which these data are collected, implications of the context on issues such as data quality, accessibility, bias and the appropriateness of use to address specific questions
- study the key issues related to ethics, security and information governance.
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, BHE), pharmaceutical companies (GSK), multinational technology companies (Microsoft Research), health-tech SMEs (Biosensors Beyond Borders), governmental agencies (Public Health England), and national clinical audit providers (Royal College of Surgeons – Clinical Effectiveness Unit, Intensive Care National Audit & Research Centre).
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.
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 the 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)
The below structure outlines the proposed modules for this programme. Module specifications provide full details about the aims and objectives of each module, what you will study and how the module is assessed. View all module specifications.
All students take five compulsory modules:
- Introduction to Health Data Science
- Health Data Management
- Epidemiology for Health Data Science
- Statistics for Health Data Science
Students take a total of four modules one from each timetable slot (Slot 1, Slot 2 etc.). The list below shows recommended modules.
- Machine Learning (compulsory)
- Data Challenge (compulsory)
- Genomics Health Data*
- Modelling & the Dynamics of Infectious Diseases
- Analysis of Hierarchical and Other Dependent Data
- Spatial Epidemiology in Public Health
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.
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 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.
The normal minimum entry requirement to be considered for master’s degrees admission at the LSHTM is at least one of the following:
- a second-class honours degree from a UK university, or an overseas qualification of an equivalent standard, in a relevant subject
- a qualification appropriate to the course of study to be followed. In this case appropriate qualifications will include mathematics, statistics, physics, engineering and computer science. Life science qualifications will be considered subject to evidence of sufficient quantitative background.
- a master’s degree in a subject appropriate to the course of study to be followed
- a professional qualification appropriate to the programme of study to be followed.
Applicants who do not satisfy these above requirements may still be admitted at the discretion of the LSHTM on the basis of their academic qualifications, work experience and references. In addition, applicants must demonstrate a high level of quantitative skills and knowledge, including: basic probability, calculus and linear algebra. They must have some prior experience of computer programming.
Applicants who have little background in some of these areas will be considered and may receive a conditional offer, subject to undertaking some preparatory learning prior to commencing the programme.
English Language Requirements
If English is not your first language, you will need to meet these requirements: Band B
Please see our English Language Requirements FAQs for information
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. Make sure to list them by order of preference as consideration will be given to your top choice first.
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 date for taught Master’s applications is as follows:
- 17 July 2020 by 23:59 (BST) for international applicants requiring a Tier 4 Student Visa, and
- 31 August 2020 by 23:59 (BST) for applicants not requiring a Tier 4 Student Visa.
A standard application fee of £50 applies to all face-to-face Master’s degree programmes and is payable upon application submission.
Tuition fee deposit
Applicants are required to respond to their Offer of Admissions 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.
Do you need a visa?
If you have EU nationality or you are from Iceland, Liechtenstein, Norway or Switzerland, you do not need immigration permission to come to the UK. You can enter, study and work in the UK without restriction. If you have dual nationality, and you choose to come to the UK using your EEA or Swiss passport, you do not need immigration permission.
For useful guidance on EEA nationals in the UK, go to the UKCISA website.
Students from outside the EEA
All non-EEA nationals who want to study in the UK must hold immigration permission that allows you to study in the UK.
If you are coming to the School to study on a full time degree programme and you have no other immigration permission for the UK, you will need to apply for a Tier 4 Student visa. You can only apply for Tier 4 when your offer at the School is unconditional.
If you already hold a Tier 4 visa for a different institution, you will probably have to apply for a Tier 4 visa for the School before you can start studying with us.