Course summary
The MSt in Healthcare Data Science course is designed to empower learners by integrating scientific principles with a comprehensive range of behavioural, managerial, and technical skills. The goal is to cultivate highly competitive professionals capable of playing effective roles in health data science projects. The design of the course considers the multidisciplinary nature of this field and incorporates required components from mathematics, statistics, computation, and health sciences to reflect the skills required for level 7 as well as incorporation of knowledge and skills outlined by industry. The MSt in Healthcare Data Science is designed for professionals and aspiring leaders who want to advance their careers at the interface of health and data science. It is particularly suitable for:
- healthcare professionals (e.g. clinicians, nurses, allied health staff, public health practitioners) who would like to enhance their technical, coding and data science skills to develop and apply data-driven approaches to improve patient care and healthcare systems
- data scientists, statisticians, and computational scientists seeking to specialise in healthcare applications and gain a deeper understanding of the medical, behavioural, and organisational contexts in which their work will be applied
- researchers and academics in medicine, biomedical sciences, or related fields who want to strengthen their quantitative and technical skills for health research
- policy makers, managers, and professionals in health organisations who require a robust understanding of health data analytics to inform evidence-based decisions, design interventions, and manage health services
- industry professionals (e.g., in biotechnology, pharmaceuticals, digital health, or medtech) who are looking to bridge scientific, technical, and healthcare knowledge to develop and deliver innovative solutions
- motivated to combine mathematical, statistical, computational, and health sciences in a multidisciplinary way
- eager to develop both technical expertise and leadership skills to contribute effectively to data science projects in health
- working professionals seeking a flexible, part-time programme that can fit alongside their careers
- committed to advancing their impact in healthcare through innovation, evidence, and collaboration
- provide teaching and learning opportunities to gain the knowledge and skills that underpin and are at the forefront of the successful implementation of an advanced health-focused data science project
- equip learners with current data science tools and techniques to manage and analyse large datasets across healthcare systems
- advance learners’ programming and analytical skills for performing meaningful and reproducible analysis
- develop, create and upskill healthcare data experts with the necessary expertise, and originality of application, to pursue and expand their roles in the context of the rapidly evolving environment of electronic health data
- promote a comprehensive understanding of the practical and ethical considerations relevant to health data, informatics and innovation
- provide work-relevant learning opportunities and practical expertise in the context of a critical awareness of current problems, best-practice, challenges, and potential solutions in the use of health data
- provide students with advanced knowledge and skills required for design and execution of the health data science project capturing: the entire process from initial curiosity driven database queries, through to data analysis, statistical inference and visualization in an impactful and reproducible output
Modules
The MSt Healthcare Data Science is a part-time Master's course designed to fit with the demands of full-time employment. The course is delivered through a combination of in-person sessions requiring attendance in Cambridge (blended with remote learning where suitable), plus self-directed learning supported through a Virtual Learning Environment (VLE). Full in-person attendance is required at the teaching blocks commencing October 2026. The Master class sessions will take place online. The course is structured across the following modules: 'Data-driven Decision-making', 'Principles of Health Data Science', 'Health Data Science II', 'Data Visualisation', 'Machine Learning', 'Databases', 'Data Analysis and Inference', 'Advanced Statistical Methods', and a Research Dissertation.
Assessment method
Each module (with the exception of the research dissertation) requires the submission of a piece of summatively assessed work which is 2,500 to 3000 words or equivalent. The research dissertation is 10,000 to 12,000 words. Each module is worth the equivalent of 15 credits of study with the exception of the dissertation which is worth 60. 15 credits is approximately equivalent to 150 hours of study which will consist of in-person teaching, blended, and self-directed learning.
How to apply
International applicants
Our courses are taught in English and require a good level of fluency. If English is not your first language, you'll need to prove you have sufficient fluency before admission. If we offer you a place, it will be subject to you meeting this requirement. As a minimum, you will be required to demonstrate an overall score of 7.5 in IELTS Academic with a minimum of 7.0 in each individual component (or equivalent). We welcome applications from international students. If you're coming from overseas, you would attend the in-person teaching sessions for this course with visitor immigration permission. It's important to be aware that entering the UK as a visitor for study purposes comes with certain expectations and restrictions, and you should fully understand the requirements.
Entry requirements
Applicants for this course are expected to have achieved a UK 2.i honours degree or equivalent. It is preferred that an applicant's first degree be in a subject relevant, or related to, life sciences, medical sciences, computational or data science.
Fees and funding
Tuition fees
| England | £20592 | Whole course |
| Northern Ireland | £20592 | Whole course |
| Scotland | £20592 | Whole course |
| Wales | £20592 | Whole course |
| International | £41184 | Whole course |
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
There is a £85 application fee
Provider information
University of Cambridge
The Old Schools
Trinity Lane
Cambridge
CB2 1TN