MSc Health Data Science and Artificial Intelligence
Learn to combine health data, advanced statistics, programming, machine learning and AI to solve real-world healthcare problems.
Key facts
- Award Masters / MSc, Postgraduate Certificate, Postgraduate Diploma
- Start date September 2027, January 2028
- Duration MSc Sept full-time: 12 months, MSc Jan full-time: 18 months, MSc part-time: 24 months
- Mode of study full time, part time
- Delivery on campus
Overview
The rapid growth of health data and artificial intelligence (AI) is transforming healthcare in the UK. The NHS has identified a need to expand its use of artificial intelligence and advanced data analysis to improve patient care and decision-making across health services (NHS Workforce Transformation report). This growing move towards tech in healthcare is increasing demand for professionals with advanced statistical, analytical and AI skills.
Why study a Masters in Health Data Science and AI?
On this Health Data Science MSc, you’ll combine advanced statistical and analytical techniques with programming and AI to investigate complex health and biomedical data. You’ll learn how to turn data into robust evidence that can support healthcare research, public health and clinical decision-making.
The course covers:
- Python programming for data analysis and visualisation;
- Mathematical and statistical methods using R;
- Advanced statistical modelling techniques for health data;
- Building predictive models using machine learning techniques;
- Methods for analysing high-dimensional datasets from electronic health records, clinical trials, registries and observational studies;
- Selecting appropriate analytical methods, critically evaluating results and producing robust evidence;
- Responsible use of generative AI in scientific, commercial and educational settings;
- Governance, ethical, legal and professional responsibilities when working with healthcare data.
Whether your background is in health, science, computing, mathematics or another relevant discipline, this MSc will help you develop specialist skills in health data science and AI.
Gain hands-on experience
Some students will have the opportunity to gain practical experience during their dissertation through placements, internships and collaborative projects with NHS or industry partners. Throughout the course, you'll explore real-world scenarios during guest lectures, group projects and problem-based learning or simulations. Everything you study will help to prepare you for real scenarios in the workplace.
Top reasons to study with us
Flexible learning
If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.
Entry requirements
Academic requirements
A minimum of a second class honours degree or equivalent in a relevant subject. Applicants without these formal qualifications but with significant appropriate/relevant work/life experience are encouraged to apply.
Your qualification will need to be in Computing, Maths and Statistics, Physical Sciences, Life and Environmental Sciences, Health and Social Sciences or closely related subject.
International entry requirements
English language requirements
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS Academic or UKVI 6.0 with a minimum of 5.5 in each sub-skill.
- Pearson Test of English (Academic) 60 overall with a minimum of 59 in each sub-skill.
- TOEFL exams taken before 21 January 2026: 80 overall with 18 in reading, 17 in writing, 17 in listening, 20 in speaking.
- TOEFL exams taken from 21 January 2026: 4 overall with no less than 4 in any band.
See our information on English language requirements for more details on the language tests we accept and options to waive these requirements.
Pre-sessional English language courses
If you need to improve your English language skills before you enter this course, University of Stirling International Study Centre offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for entry to this degree.
Find out more about our pre-sessional English language courses.
Course details
Modules
Compulsory modules (timing based on full time course)
| Yr 1, semester 1 - Autumn | Python for Data Science (ITNPBD2) | 20 credits |
| Yr 1, semester 1 - Autumn | Applying Generative AI (ITNPBD4) | 20 credits |
| Yr 1, semester 1 - Autumn | Statistics for Data Science (MATPMDA) | 20 credits |
| Yr 1, semester 2 - Spring | Advanced Health Statistics (MATPMDH) | 20 credits |
| Yr 1, semester 3 - Summer | Dissertation Project (ITNPBD5) | 60 credits |
Year 1 options, semester 2 - Spring
| Year 1 options | Machine Learning (ITNPBD6) | 20 credits |
| Year 1 options | Relational and non-Relational Databases (ITNPBD3) | 20 credits |
| Year 1 options | Applied Epidemiology (MPHP004) | 20 credits |
Teaching
Teaching is carried out through lectures, seminars, guest speakers, article discussion groups, and presentations.
Assessment
You’ll be assessed by combination of exams and coursework, including written assignments and presentations. The final assessment on the course involves a dissertation.
Course director
Fees and funding
|
2027/28 |
|
|---|---|
| UK and Republic of Ireland students | £11,800 |
| International (including EU) students | £24,300 |
Postgraduate tuition fee loans
This course is eligible for a postgraduate tuition fee loan from one of the UK’s governments. See the Scholarships and funding section, below, for more details.
Fee information
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, the total course fee will be split over the years that you study. The total fee will remain the same and will be held at the rate set in your year of entry.
Additional costs
There are some instances where additional fees may apply. Depending on your chosen course, you may need to pay additional costs, for example for field trips. Learn more about additional fees.
Scholarships and funding
Funding
Learn more about loans and funding opportunities or use our scholarship finder to explore our range of scholarships.
Cost of living
If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs. This usually takes the form of student loans, grants or bursaries, and the amount awarded depends upon your personal circumstances and household income.
International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies. You should contact the relevant authority in your country to find out if you’re eligible to receive support.
Payment options
We aim to be as flexible as possible, and offer a wide range of payment methods—including the option to pay fees by instalments. Learn more about how to pay
After you graduate
Healthcare providers, public health organisations, pharmaceutical companies and health technology businesses are increasingly seeking professionals who can analyse complex health data and apply AI responsibly to support decision-making.
Graduates from this health data science Masters leave with the knowledge and practical skills to analyse complex health and biomedical data. Also to apply AI to address real-world challenges in healthcare, public health, and research.
This MSc could prepare you for roles such as:
- health data scientist;
- clinical data analyst;
- Healthcare informatics specialist;
- clinical trials data analyst;
- digital health specialist;
- epidemiological data analyst;
- population health analyst.
You could work in sectors such as:
- the NHS;
- health technology;
- the biopharmaceutical industry;
- medical technology;
- public health;
- research organisations.
The average salary for a healthcare data scientist in the UK is £44,382 (indeed.com Aug 2026).