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MSc Health Data Analytics

Key facts

Start date September 2019

Duration/mode 12 months full time, 24 months part time

UK/EU fees £10,500 (total)

International fees £22,750 (total)

Entry requirements A bachelor degree with a 2:1 (hons) in a relevant subject.

Language requirements

IELTS 7.0 overall, with no less than 6.0 in writing and 6.5 in all other components


Most funding bodies in medicine and some in other disciplines have highlighted the need for advanced analytical training in population health research.

This course, is the only taught postgraduate course in the UK that specialises in the analysis of observational studies, routine healthcare data, and that adopts a focus on causal inference.

The course offers intensive training in data analytic techniques tailored to the needs of career enhancers and career changers with a focus on health. It can be studied full time over 12 months or part time over 24 months.

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Course content

Full time MSc students will study modules totalling 180 credits over 12 months. If you study part time you will study fewer modules in each year.

You will take compulsory modules, including our innovative Professional Skills for Health Data Analysts module. The course is designed to give you the skills and experience to work effectively in research, public health or health services research. It covers; ethics, academic writing for publication, consultancy, management and leadership skills.

The course will train scientists in the cutting-edge quantitative skills needed for health research. You'll develop the proficient expertise required to be able to work in a variety of fields related to health. You'll also gain in-depth knowledge and will be nurtured in the type of thinking that yields the ability to undertake robust scientific enquiry using health data of various kinds.

The course will provide strong foundations in the skills and knowledge of data analytics with relevance to health. We stretch you to acquire and implement advanced techniques through optional modules. These modules allow your learning to be tailored towards discipline-specific paths appropriate to your future career.

By graduation, you'll be at the forefront of the discipline of health data analytics, with advanced knowledge and skills appropriate to careers involving observational health data.

Distinctive features of the course include:

  • A focus on statistical methods for observational health and health services research;
  • State-of-the-art training in predictive modelling;
  • Cutting-edge training in causal inference modelling (unique for UK MSc programmes);
  • Leading expert training in the pitfalls and malpractices of observational data analysis (unique for PGT programmes world-wide);
  • Extensive access to practice and practice-derived datasets maintained within Leeds Institute of Data Analytics (LIDA);
  • Substantial scope for student choice across a range of optional modules to accommodate different interests and needs, including potential engagement with the health-orientated non-medical aspects of computing and geography (via modules and research projects);
  • A compulsory generic and transferable skills module to prepare graduates for professional careers as independent researchers;
  • Research projects using clinically-relevant data, supervised by research-active academics, leading to the production of journal papers suitable for publication;
  • The use of blended learning to meet the differing learning styles of individual students, and to provide student paced-learning for those with different aptitudes for quantitative skills training.

Course structure

These are typical modules/components studied and may change from time to time. Read more in our Terms and conditions.

For more information on typical modules, read Health Data Analytics MSc Full Time in the course catalogue

For more information on typical modules, read Health Data Analytics MSc Part Time in the course catalogue

Learning and teaching

We mix face-to-face teaching with technology to enhance your learning experience. Self-directed online learning lets you study at a pace that suits you, whilst face-to-face support allows you to explore individual areas of difficulty and extend your understanding.

You’re likely to experience:

  • small-group teaching with an expert in the field, including some modules with the opportunity to mix with students from other disciplines;
  • teaching in computer clusters to help you rapidly gain the skills required with statistical packages;
  • online workbooks with relevant links for further research;
  • online audio-visual presentations (vodcasts);
  • online help files and sample data sets with worked examples, which support all the statistical packages;
  • experiential learning as part of the research team for your research project;
  • continuous formative and summative assessment, and feedback.


We understand the importance of assessment and feedback in your learning. We provide assessment in as many modules as possible so that you can gauge your understanding of the key concepts.

You’ll get feedback in a variety of ways. These include:

  • informal discussion with tutors
  • written feedback from formative assessments
  • marks obtained in both formative and summative assessments
  • peer-review from presenting projects and data.

Each module contains a summative assessment component. Some of these will be done via continuous in-course assessment, and some as end-of-module assessment.

Our assessment and feedback will use a number of methods:

  • Online assessment which allows a flexible set of responses, marks the assessment immediately and provides both results and more structured feedback;
  • Short answer questions to test understanding of more complex methods and scenarios;
  • Project reports that allow deeper exploration of a topic;
  • Other methods to fit the skills and knowledge under test, eg presentation of data;
  • For the overall research project, regular meetings with your supervisor to monitor your progress and give feedback.

The MSc Health Data Analytics course at the University of Leeds is the only taught postgraduate programme in the UK that specialises in the analysis of observational studies, routine healthcare data, and that adopts a focus on causal inference. Back to top

Applying, fees and funding

Entry requirements

A 1st class degree in a quantitative or scientific subject area with substantial mathematical, statistical or numeracy components (at least at 2:1 standard). We also consider working experience (two years or more) of research in a quantitative subject area.

Non-graduates who fulfil all of the below criteria:

  • successfully completed three years of a UK medical degree
  • are normally ranked in the top 50% of the year 3 cohort
  • wish to take the Health Data Analytics MSc as an intercalated programme

will also be accepted.

English language requirements

IELTS 7.0 overall, with no less than 6.0 in writing and 6.5 in all other components. For other English qualifications, read English language equivalent qualifications.

International students who do not meet the English language requirements for the programme may be able to study an English for Academic Purposes pre-sessional course with a progression route to the degree programme. For information and entry requirements, read Pre-sessional programmes.


How to apply

Apply (Full time)
Apply (Part time)

This link takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.

Admissions policy

Link to admissions policy document


UK/EU fees: £10,500 (total)
International fees: £22,750 (total)

Read more about paying fees and charges.

For fees information for international taught postgraduate students, read Masters fees.

Part-time fees are normally calculated based on the number of credits you study in a year compared to the equivalent full-time course. For example, if you study half the course credits in a year, you will pay half the full-time course fees for that year.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

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Career opportunities

There is demand for students and academic staff with excellent statistical skills, an enquiring attitude, and a broader understanding of the research environment. Our graduates are attractive to employers in academic research, health and social care and industry. Prospective employers value their technical expertise and research understanding. They also value the professional skills gained, including writing a grant application and a paper of submission quality.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

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