Health Data Science (MSc)
Introduction
Health Data Science combines health research, statistics and computing sciences to address health and care problems using data. Our MSc programme enables students from both healthcare and computational backgrounds to develop their health data science skills, supported by an interdisciplinary team of academics, NHS and industrial partners. 10% NHS staff discount.
MSc Health Data Science is also available to study part-time online.
Nationally and internationally there is a critical shortage in data intensive analytic capacity applied to healthcare. The effective and efficient use of data has the potential to create the transformative step change needed through targeting health and care improvement.
Our interdisciplinary MSc in Health Data Science aims to develop the next generation of health data scientists. The programme is delivered by academics from our Aberdeen Centre for Health Data Science (ACHDS). The Centre for Health Data Science aims are to create innovative, interdisciplinary, data science solutions to the big challenges for health and health care, to improve health for individuals, local communities and globally.
The programme offers a wide range of specialist elective options to allow students to build a personalised masters depending on their background, interests and skills and includes a work-based placement or research project. At the end of the programme students will be able to evaluate, critique and demonstrate competency in the practical application of current data intensive analytical methods and current health and care research methods.
The MSc is ideally suited to healthcare professionals who wish to develop data health science skills or for students from computational and/or data intensive science backgrounds who wish to work in the health sector.
What You'll Study
- Stage 1
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Stage 1: Compulsory Courses
- Applied Statistics (PU5017)
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15 Credit Points
This course in Applied Statistics focuses on the application of statistical techniques in postgraduate research for health professionals, with a particular emphasis on the correct interpretation of statistical analyses results. The course will NOT focus on the statistical theory underlying the subject. An important component of the course is the use of a statistical package (IBM SPSS), which can be used to implement all the methods taught on this course.
- Getting Started at the University of Aberdeen (PD5006)
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This course, which is prescribed for all taught postgraduate students, is studied entirely online, takes approximately 2-3 hours to complete and can be taken in one sitting, or spread across the first 4 weeks of term.
Topics include University orientation overview, equality & diversity, MySkills, health, safety and cyber security, and academic integrity.
Successful completion of this course will be recorded on your Transcript as ‘Achieved’.
- Introduction to Health Data Science (PU5063)
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15 Credit Points
Nationally and internationally there is recognition of the critical shortage in data-intensive analytic capacity applied to healthcare. This course is an introduction to the field of health data science, with examples of real-life healthcare applications, using the popular data science language R.
Stage 1: Optional Courses
Students select TWO courses from the following:
- Epidemiology (PU5030)
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15 Credit Points
This course in applied epidemiology gives an introduction to disease measurement at a population level, basic epidemiological study design and analysis, and provides an understanding of key methodological issues needed to apply when designing – or critically appraising – an epidemiological study.
- Database Systems and Big Data (CS5097)
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15 Credit Points
This course will be of interest to anyone who wishes to learn to design and query databases. The course aims to teach the material using case studies from real-world applications. You will develop a critical understanding of the principal theories, principles and concepts, such as modelling techniques used in the design, administration and security of database systems. You will also learn core theoretical concepts such as relational algebra, file organisation and indexing. At the end of this course you will be able to design and build Web and cloud-based databases and have a critical understanding of how database-driven applications operate.
- Fundamentals of Research Design (PU5052)
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15 Credit Points
This course introduces you to health research methods, focusing on designing strong research proposals. You'll learn to formulate research questions, choose study designs, identify outcomes, and plan data collection.
We will explore key study designs, from experimental to observational, and master sampling and data collection for both qualitative and quantitative research. You'll also develop skills in critical appraisal and research ethics, equipping you to design rigorous and impactful research.
- Designing Real - World Trials (PU5068)
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15 Credit Points
This course will focus on trials in the evaluation of real-world healthcare and public health settings. The course is run by staff from our world-leading Centre for Healthcare Randomised Trials (CHaRT) and the Aberdeen Centre for Evaluation - awarded the Queen's Anniversary Award for sustained excellence in health services research. Through studying this course, you will develop the knowledge and awareness of how to design a fair test, the appropriate use of trials and alternative trial designs, involving patients and the public, and sample size considerations.
- Stage 2
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Stage 2: Compulsory Courses
Students must take the following courses:
- Health Informatics (PU5565)
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15 Credit Points
We live in a time of ‘Big Data’ with the rapid growth in the digital capture of health information. Health Informatics is the science of data capture, linkage and analysis of large datasets to improve health. The demand for health researchers with training and experience in health informatics is high. For people practicing in Public Health, it is a key skill. It will equip students for any career in health research or public health practice and this course is an excellent stepping stone for those wishing to develop a specialist interest in the field.
- Machine Learning for Healthcare (PU5567)
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15 Credit Points
Machine learning has the potential to revolutionise healthcare. The aim of this course is to introduce machine learning for health data science with examples of real-life healthcare applications, using the popular data science language R.
Stage 2: Optional Courses
Students must select TWO courses from the following:
- PU5576: Systematic Reviews for Clinical Practice and Health Policy
Please note that PU5548: Work-based Placement in Applied Health Sciences can not be taken with courses PU5930 or PU5926.
- Work - Based Placement in Applied Health Sciences (PU5548)
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15 Credit Points
This work-based placement elective offers a professional placement with a government/public, industrial, civic or voluntary health and/or development sector organisation. You will undertake a ten-week placement with your host organisation, either within the organisation, remotely from Aberdeen, or using a combination of both. Placements are subject to availability and may be offered on a competitive basis. We reserve the right to remove a student from placement should an employer report any inappropriate behaviour or unacceptable work. Should this happen, University-based remedial training supervised by course staff will be offered as an alternative activity and assessments will remain in place but will be capped at D3.
- Health Systems and Policy Research (BU5594)
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15 Credit Points
The course aims to provide foundational knowledge while placing emphasis on fostering critical thinking about the key challenges confronting health systems and the strategies to enhance health. With a global perspective, it examines diverse healthcare systems, encouraging students to compare, analyse, and critique them. Topics include the impact of social inequalities on health disparities and their implications for social policy, the use of charges for health care and their impact on health care use and health as well as public health approaches and their connections to issues such as unemployment and obesity.
- Understanding and Applying Regression Models (PU5569)
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15 Credit Points
This intermediate-level course intends to advance a student's statistical skills and understanding of common and more advanced regression modelling techniques so that they can apply them to a wide range of health research data. The course will focus on introducing the student to the concepts underpinning generalised linear models. They will deepen their understanding of linear and logistic regression and learn how to analyse outcomes such as count data and time-to-event data using regression for count data and survival analysis. This course will focus on the application, interpretation, and communication of the learned methodologies. It assumes that students will already have completed a first course in introductory statistics and have an understanding of hypothesis testing and basic mathematical skills.
We strongly recommend signing up for this course only if you have solid knowledge and experience of basic statistical concepts and methodologies used for descriptive statistics (e.g. mean, standard deviation and other measures on central tendency and dispersion) and statistical inference (e.g. standard error, confidence intervals, hypothesis tests such as t-test and ANOVA). Knowledge or experience of simple linear regression is preferable but not essential.
- Health Economics (PU5571)
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15 Credit Points
Resources available for the provision and payment for health care are limited. However, knowledge of economics helps ensure that available resources are used in the most effective way possible. Economics allows more informed decision making about a variety of issues: choosing between alternative treatments; setting priorities between patients; choosing between alternative new technologies; organising the provision of health care.
In this course students will acquire a knowledge and understanding of:
- Key themes of economic theory applied to health care
- Some of the main techniques of health care evaluation
- Main arguments concerning alternative systems for organising and financing health care
- Data Science: from Data to Insight (CS5703)
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15 Credit Points
Data Science is an interdisciplinary field that seeks to identify and understand phenomena captured in structured or unstructured data, extract insights, and add value by generating predictions that aid optimization of processes and equipment. These techniques show considerable promise for bringing about a revolution, increasing the significance and value of owning and collecting data of all types. This course introduces the common techniques and considers the implications for data managers.
- Stage 3
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Stage 3: Optional Courses
Select either the 60 credit course or two 30 credit courses:
- Masters Research Project (PU5922) (60 credits)
OR
- Professional Placement in Health Data Science (PU5926) (60 credits)
OR
- Evaluating policy effects in practice (PU5925) (30 credits)
- Enhanced Work-Based Placement in Applied Health Sciences (PU59 ) (3030 credits)
- Masters Research Project (PU5922)
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60 Credit Points
This course offers students the opportunity to complete a substantial piece of data-driven, empirical work within their field of study under the supervision of an experienced researcher.
Topics available will be varied but within the domain of their field of study. Alongside supervisors, students will identify a suitable topic area, describe an appropriate study design and implement an empirical study. Students will be involved alongside the supervisors in the process of defining the research question, and developing the research plan and, where appropriate, obtaining regulatory approvals. This course is for non-laboratory based projects (if you are intending to undertake a project in a scientific laboratory setting, you should register on MB5904).
- Professional Placement in Health Data Science (PU5926)
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60 Credit Points
This work-based placement elective offers a professional placement with a civic, government, industrial, public, research or voluntary health and/or development sector organisation in the field of Health Data Science. You will undertake a ten-week placement with your host organisation, either within the organisation, remotely from Aberdeen, or using a combination of both. Placements are subject to availability and are offered on a best match basis.
We will endeavour to make all course options available. However, these may be subject to change - see our Student Terms and Conditions page. In exceptional circumstances there may be additional fees associated with specialist courses, for example field trips.
Fees
- UK
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- Tuition Fees for 2025/26 Academic Year
- £11,100
- Tuition Fees for 2026/27 Academic Year
- £11,100
- Tuition Fees for 2025/26 Academic Year (University of Aberdeen Graduates *)
- £7,000
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University of Aberdeen graduates are eligible for the Alumni Postgraduate Scholarship, reducing tuition fees to £7,000 - matching the current SAAS tuition loan - See full terms and conditions
- Tuition Fees for 2026/27 Academic Year (University of Aberdeen Graduates *)
- £7,000
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University of Aberdeen graduates are eligible for the Alumni Postgraduate Scholarship, reducing tuition fees to £7,000 - matching the current SAAS tuition loan - See full terms and conditions
- EU / International students
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- Tuition Fees for 2025/26 Academic Year
- £23,000
- Tuition Fees for 2026/27 Academic Year
- £23,000
- Tuition Fees for 2025/26 Academic Year (Self-funded Students *)
- £15,000
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The above fee includes the £8,000 Aberdeen Global Scholarship provided to self-funded international students. Full terms and conditions apply.
- Tuition Fees for 2026/27 Academic Year (Self-funded Students *)
- £15,000
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The above fee includes the £8,000 Aberdeen Global Scholarship provided to self-funded international students. Full terms and conditions apply.
Funding Opportunities
NHS Staff Discount: the University of Aberdeen offers a 10% discount for NHS staff studying this programme.
Alumni Discount Scheme - we are pleased to offer a 20% discount for postgraduate tuition fees to all alumni who have an undergraduate degree from University of Aberdeen.
Please note that the Aberdeen Alumni Discount cannot be claimed in conjunction with any other scholarship award.
Scholarships
All eligible self-funded international Postgraduate Masters students will receive an £8,000 scholarship. Learn more about this Aberdeen Global Scholarship here.
To see our full range of scholarships, visit our Funding Database.
How You'll Study
The programme will involve a variety of teaching methods including face to face lectures, tutorials, PowerPoint videos with accompanying self-tests and quizzes, video interviews with accompanying guides, computer-based practical sessions, self-study of recommended reading material and discussion boards. This mixed approach to teaching ensures that a range of different learning opportunities are provided for all students.
Learning Methods
- E-learning
- Group Projects
- Individual Projects
- Lectures
- Peer Learning
- Professional Placements
- Research
- Seminars
- Tutorials
- Workshops
Assessment Methods
A variety of different approaches are combined to assess student understanding, progress and performance throughout the programme. Both formative and summative assessments include reflective learning, writing computer programmes, written and activity-based assessments, structured and multiple-choice questions. Whenever possible, the assessment will utilise real life scenarios and/or data and equip the student with transferable skills for subsequent careers.
Why Study Health Data Science?
- The programme is delivered by staff from our Institute of Applied Health Sciences, a large multidisciplinary grouping of University staff and the Aberdeen Centre for Health Data Science (ACHDS). The ACHDS has an established global reputation in the health and data sciences harnessing academia, NHS, industry and public partnerships.
- Courses will be taught by academics and international experts from the Schools of Medicine, Medical Sciences and Nutrition, Natural and Computing Science and Business, the NHS and industry giving students the opportunity to learn from an interdisciplinary team.
- Students will have the opportunity to participate in a student-led workshop series throughout the programme, mentored by members of the ACHDS team. Students will work with our NHS, local authority, industry and innovation partners to apply their skills and knowledge to real world scenarios.
- At the end of the programme, students will be asked to coordinate and deliver a showcase symposium which will be live streamed. They will present their project work and network with partners and collaborators. Building transferable skills, the students will have opportunities in leadership, communication, event planning and, with the commitment of our partners, a key opportunity to network.
- Enhancing student’s employability is a key focus of the programme and engagement with potential employers will be facilitated by our existing partnerships with companies and public bodies including the NHS and Opportunity North East (ONE) business development framework.
Interested in this programme?
What Our Students Say
Entry Requirements
Qualifications
The information below is provided as a guide only and does not guarantee entry to the University of Aberdeen.
Applicants will need an undergraduate degree at a minimum of 2:2 or equivalent in a relevant discipline including life sciences, medicine, computing and maths.
Please enter your country or territory to view relevant entry requirements.
English Language Requirements
To study for a Postgraduate Taught degree at the University of Aberdeen it is essential that you can speak, understand, read, and write English fluently. The minimum requirements for this degree are as follows:
IELTS Academic:
OVERALL - 6.5 with: Listening - 5.5; Reading - 6.0; Speaking - 5.5; Writing - 6.0
TOEFL iBT:
OVERALL - 90 with: Listening - 17; Reading - 21; Speaking - 20; Writing - 21
PTE Academic:
OVERALL - 62 with: Listening - 59; Reading - 59; Speaking - 59; Writing - 59
Cambridge English B2 First, C1 Advanced or C2 Proficiency:
OVERALL - 176 with: Listening - 162; Reading - 169; Speaking - 162; Writing - 169
Read more about specific English Language requirements here.
Document Requirements
You will be required to supply the following documentation with your application as proof you meet the entry requirements of this degree programme. If you have not yet completed your current programme of study, then you can still apply and you can provide your Degree Certificate at a later date.
- CV
- an up-to-date CV/Resumé
- Degree Certificate
- a degree certificate showing your qualifications
- Degree Transcript
- a full transcript showing all the subjects you studied and the marks you have achieved in your degree(s) (original & official English translation)
- Personal Statement
- a detailed personal statement explaining your motivation for this particular programme
Careers
Health Data Science is a rapid growth area and the Academy for Medical Sciences and Health Foundation have both identified the significant shortage of skilled workforce in this field. This shortage is recognised in both the UK and internationally.
Graduates will have the skills needed for a range of careers in Academia, NHS and Industry that involve the analysis and interpretation of health data. Students completing this programme with a commendation or above would also be eligible for consideration to undertake PhD study in this area.
Industry Links
Enhancing student’s employability is a key focus of the programme and engagement with potential employers will be facilitated by our existing partnerships with companies and public bodies including the NHS and Opportunity North East (ONE) business development framework.
Our Experts
- Programme Coordinator
- Caroline Franco
- Other Experts
- Dr Kathryn Martin
- Dr Mintu Nath
- Dr Heather Morgan
- Professor Nir Oren
- Professor Lesley Anderson
Information About Staff Changes
You will be taught by a range of experts including professors, lecturers, teaching fellows and postgraduate tutors. However, these may be subject to change - see our Student Terms and Conditions page.
Facilities
Get in Touch
Contact Details
- Address
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Student Recruitment & Admissions
University of Aberdeen
University Office
Regent Walk
Aberdeen
AB24 3FX