Health Data Science MSc/PGDip/PGCert

Start date
1 year full-time, 2 years part-time
Course Type
Postgraduate, Taught
Annual tuition fee for 2023/24:
UK: £10,170 full-time
International: £26,640 full-time
More details on fees and funding
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This Masters programme is aimed at graduates with interests in artificial intelligence, health data and advanced computational approaches in the clinical and biomedical space. 


Book a 1-1 meeting with your Admissions Tutor

You can now book a 1-1 appointment with your Admissions Tutors for MSc Health Data Science. Our academics are available on Zoom on Mondays from 10am - 11am. This is your chance to ask any questions you may have about the course.

Book your place now  

It will equip future health data scientists with the knowledge and skills to perform analyses and develop novel tools and methods for this rapidly growing field. It is aimed at students with diverse backgrounds from biomedical/medical domains, including clinical trainees, as well as computer science, mathematics and statistics to conduct their own analyses, and also to create the next generation of cutting-edge health data scientists who will be able to develop new tools and methods matching the latest technological advancements.

Students will learn about the breadth of health data science and its applications, and they will be taught how to design, perform and enhance analyses with the appropriate methods and technologies to address practical medical and clinical questions. Students will also benefit from training in areas such as clinical bioinformatics, health informatics, epidemiology, clinical systems, integrated multimodal data analysis and omics analytics for health data science careers in academia, industry and national health services.

Programme Leads

Dr Andreas Karwath

Andreas Karwath profile pictureDr Karwath is an Associate Professor in the Institute of Cancer and Genomic Sciences and the deputy programme lead for the MSc in Health Data Science. His research interests focus on the integration of clinical data and the extraction of information and patterns from this combined information source using modern AI techniques, such as variational autoencoders (VAEs). He is also interested in cancer risk prediction, application of AI to Diabetes and clinical procedures, predictive toxicology, and the application of learning to rank, predictive toxicology.

 View Dr Karwath's staff profile. 

Professor Georgios V. Gkoutos

George Gkoutos profile pictureProfessor Gkoutos is an Associate Director of Health Data Research UK and holds the chair of Clinical Bioinformatics, a joint appointment between the University of Birmingham Medical School and the University Hospitals Birmingham NHS Foundation Trust.

View Professor Gkoutos' staff profile. 


Overall, I have learnt the most in the last six months of my life. I have progressed way beyond what I expected in my coding skills, ability to present and pick up new skills and concepts quickly.

MSc Health Data Science student

Why study this course?

Students on the Health Data Science programme will:

  • be embedded within a diverse, collaborative, interdisciplinary environment, incorporating academia, industry and healthcare.
  • acquire skills in governing health data science, its foundations and effective application within healthcare settings.
  • develop an in-depth understanding of healthcare systems, their underlying ethics and their governance structures. Students will also explore the role of current and potential future applications of health data science in the delivery of patient-centred care, patient-provider interactions and wider aspects of healthcare delivery.
  • understand how health data science skills can revolutionise healthcare data and patient-specific genome information for research, clinical care and innovation in the 21st century.
  • learn the value of different types of health information, systems and integration, and the role of information related technologies in delivering healthcare.
  • gain practical experience of working within diverse, multi-disciplinary environments across the healthcare sector and its associated industries, and develop effective communication and delivery skills within the wider landscape.
  • enhance their prospects. 80% of MSc Health Data Science students have received an offer for a PhD or job before finishing their thesis (2022).


  • Foundations of Computing Practices in Health Data Science (20 credits)
  • Essentials of Mathematics and Statistics (20 credits)
  • Data Analytics & Statistical Machine Learning (20 credits)
  • Health Data Fundamentals (20 credits)
  • Epidemiology and Health Informatics (20 credits)
  • Integrative Multimodal Data Analytics (20 credits)
  • Interdisciplinary Health Data Research Project (60 credits)




  • UK: £10,170 full-time, £5,085 part-time
  • International: £26,640 full-time

Are you an international applicant?

All international applicants to this course will be required to pay a non-refundable deposit of £2,000 on receipt of an offer, to secure their place.

Find out more about the deposit >>.


Postgraduate Loans for Masters students

As a UK resident you can apply for a government loan for postgraduate Masters study. This is a contribution towards the costs of study and whether the loan is used towards fees, maintenance or other costs will be at the discretion of the student.

Find out more about the Postgraduate Loan.

How To Apply

How to apply for our taught postgraduate programmes

Application deadlines

The deadline for international students (including EU) to apply is 1 July 2023. The deadline for UK students is 31 August 2023.

Making your application

How to apply

To apply for a postgraduate taught programme, you will need to submit your application and supporting documents online. We have put together some helpful information on the taught programme application process and supporting documents on our how to apply page. Please read this information carefully before completing your application.

Apply now

Our Standard Requirements

A 2:1 undergraduate honours degree in a medical/life science (medicine, biology, chemistry, etc.) or quantitative science subject (computer science, mathematics, physics, etc.). Equivalent relevant work experience will also be considered for eligibility to enter the programme. 

Mathematics for Data Science Pre-sessional Bootcamp

To accompany the support offered to the under-represented groups that the AI and Data Science Conversion Masters Scholarship will benefit, we are offering a Mathematics for Data Science Pre-sessional Bootcamp to successful awardees. This pre-sessional course provides an alternative means of entry for those who may not meet the standard Maths entry requirement of the courses.

Admission to this bootcamp is made as part of your scholarship application.

Apply now  

International students

Academic requirements

We accept a range of international qualifications - use the dropdown box below to select your country and see the equivalencies to the above UK requirements.

English language requirements

IELTS 6.5 with no less than 6.0 in any band.

If you are made an offer of a place to study and you do not already meet the language requirement, you have the option to enrol on our English for Academic Purposes Presessional Course. If you successfully complete this, you will be able to fulfil the language requirement without needing to take a further qualification. 

International Requirements

Course delivery:

We have two teaching semesters per year, the autumn semester and spring semester. Semester dates can be found on our website.

Full-time students will typically take three modules in each semester, followed by a dissertation. The modules are delivered in block-teaching style (between 2-3 weeks) and students can be expected to require 10-15 hours of classroom time per week. Part-time students will typically take three modules across each year, followed by a dissertation for MSc students.

Each module represents a total of 200 hours of study time, including preparatory reading, self-guided study and assignment preparation.

Assessment Methods

Students will be assessed through a variety of methods, including essays, exams, oral presentations, computer-based problem-solving exercises and a thesis.

This programme will give students clear and compelling experience of working across academic, NHS and industry sectors, with extensive supervisory and mentoring arrangements to maximise their exposure to these environments. Not only will this prepare them mentally/practically, but also help identify specific opportunities/contacts for progress into relevant career pathways.

University Careers Network

Preparation for your career should be one of the first things you think about as you start university. Whether you have a clear idea of where your future aspirations lie or want to consider the broad range of opportunities available once you have a Birmingham degree, our Careers Network can help you achieve your goal.

Our unique careers guidance service is tailored to your academic subject area, offering a specialised team (in each of the five academic colleges) who can give you expert advice. Our team source exclusive work experience opportunities to help you stand out amongst the competition, with mentoring, global internships and placements available to you. Once you have a career in your sights, one-to-one support with CVs and job applications will help give you the edge.

If you make the most of the wide range of services you will be able to develop your career from the moment you arrive.

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