Health Data Science, MSc

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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.

Study Information

At a Glance

Learning Mode
On Campus Learning
Degree Qualification
MSc
Duration
12 months or 24 months
Study Mode
Full Time or Part Time
Start Month
September
Location of Study
Aberdeen

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

Compulsory Courses

Applied Statistics (PU5017)

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)

This course, which is prescribed for all taught postgraduate students, is studied entirely online, takes approximately 5-6 hours to complete and can be taken in one sitting, or spread across a number of weeks.

Topics include orientation overview, equality and diversity, health, safety and cyber security and how to make the most of your time at university in relation to careers and employability.

Successful completion of this course will be recorded on your Enhanced Transcript as ‘Achieved’.

Introduction to Health Data Science (PU5063)

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.

Optional Courses

Students select TWO courses from the following:

Epidemiology (PU5030)

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)

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)

15 Credit Points

Fundamentals of research design provides the student with skills in both quantitative and qualitative design enabling the student to plan ethical research in a health context. Students are taken through each step - from formulating the research question, to study design, sample selection, methods for data collection to dissemination of results.

Upon completion of this course you will be able to:

  1. Summarise the key factors involved in the research process
  2. Evaluate the appropriateness of study designs commonly used in applied health research studies
  3. Identify the advantages and disadvantages associated with quantitative and qualitative research methodologies
  4. Develop a research proposal to answer a health-related research question which maximises research quality and rigour.
Health Economics (PU5032)

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
Designing Real - World Trials (PU5068)

15 Credit Points

Randomised Controlled Trials (RCTs) are used to test the effectiveness of interventions. The aim of this course is to take a student through the process of designing RCTs. The course will focus on RCTs in the evaluation of real-world healthcare and public health settings.

Upon completion of this course, students will be able to:

1. Specify and critically evaluate the key elements of trial design.

2. Justify trial design decisions.

3. Describe the differences between pragmatic and explanatory trials.

Stage 2

Compulsory Courses

Students must take the following courses:

Health Informatics (PU5565)

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)

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.

Optional Courses

Students must select TWO courses from the following:

Data Science: from Data to Insight (CS5703)

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.

Systematic Reviewing (PU5526)

15 Credit Points

This course will equip students with the relevant skills to interpret and conduct systematic reviews on the effectiveness of healthcare interventions. Using lectures and practical sessions, students will understand the principles of systematic reviewing and the differences between narrative and systematic reviews. They will learn to formulate a clear research question and undertake each stage of systematic reviewing of randomised controlled trials. They will also learn about the importance of the levels of evidence and systematic reviews of other different study designs. This course will also introduce the students to advances in systematic reviews such as network meta-analysis and use of Individual Patient Data (IPD)

Work - Based Placement in Applied Health Sciences (PU5548)

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.

Health Systems and Policy Research (BU5594)

15 Credit Points

The course aims to instill knowledge but, much more importantly, stimulate students’ thinking about the major challenges within different health systems and the options for the health services management. Furthermore, it aims to take a genuinely international perspective on health care, providing knowledge of different health care systems and encouraging comparison and critique. It covers a wide variety of topics including an overview of the health systems around the world, the effects of social inequalities on health inequalities and their repercussions for social policy and issues of public health policy towards tobacco, alcohol and obesity.

Understanding and Applying Regression Models (PU5569)

15 Credit Points

This course intends to develop a student’s statistical skills and understanding so that they can apply common multivariate regression modelling techniques to a range of health research data. The course will focus on the application, interpretation and communication of common regression models, including general linear models, log-linear models, logistic regression, and survival analysis. It assumes that students will already have completed a first course in statistics and have an understanding of bivariate techniques and basic mathematical skills.

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)
  • Extended Work-Based Placement in Applied Health Sciences (PU5923 ) (30 credits)
Masters Research Project (PU5922)

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 to be completed within a laboratory setting. 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 MB5913)

Extended Work - Based Placement in Applied Health Sciences (PU5923)

30 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. 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.

Fee information
Fee category Cost
EU / International students £23,000
Tuition Fees for 2025/26 Academic Year
UK £11,100
Tuition Fees for 2024/25 Academic Year

Fee Information

Additional Fee Information

  • In exceptional circumstances there may be additional fees associated with specialist courses, for example field trips. Any additional fees for a course can be found in our Catalogue of Courses.
  • For more information about tuition fees for this programme, including payment plans and our refund policy, please visit our Tuition Fees page.

Funding Opportunities

NHS Staff Discount: the University of Aberdeen offers a 10% discount for NHS staff studying this programme. Learn more here.

Scholarships

Self-funded international students enrolling on Postgraduate Taught (PGT) programmes for January 2025 will receive one of our Aberdeen Global Scholarships, ranging from £3,000 to £8,000, depending on your domicile country. Learn more about these Aberdeen Global Scholarships here.

From September 2025 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.

What Our Students Say

Andrea Canale

Andrea Canale

Andrea Canale

After working in the oil and gas industry since graduating first time around in 2002, completing MSc Health Data Science at the University of Aberdeen has allowed me to accomplish my goal of gaining a role in public health within NHS Grampian.

Lorna Henderson

Lorna Henderson

Lorna Henderson

My favourite part of the degree has been learning new skills from lecturers with real-life experience of solving data science challenges. My classmates are friendly and come from a range of backgrounds, giving a rich and diverse learning experience.

Entry Requirements

Qualifications

The information below is provided as a guide only and does not guarantee entry to the University of Aberdeen.

Applicants will usually possess an undergraduate degree at a minimum of 2:1 or equivalent in a relevant discipline including life sciences, medicine, computing and maths. Other relevant work experience will also be considered.

Please enter your country to view country-specific 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.

Image for useful fact about this Subject

Top 15 UK University

The University of Aberdeen is ranked 12th in the UK in the Guardian University Guide 2025 and 15th in the Times and Sunday Times Good University Guide 2025

Our Experts

Other Experts
Dr Kathryn Martin, The University of Aberdeen
Dr Mintu Nath, The University of Aberdeen
Dr Heather Morgan, The University of Aberdeen
Professor Nir Oren, The University of Aberdeen
Professor Lesley Anderson, The University of Aberdeen
Programme Coordinator
Dr Dimitra Blana, The University of Aberdeen

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

Image for Health Sciences Building
Health Sciences Building

Health Sciences Building

The Health Sciences building, located on the Foresterhill Health Campus, houses the purpose built Clinical Research Facility, researchers from the Institute of Applied Health Sciences and the Imaging Department which boasts state-of-the-art equipment

Image for Foresterhill Health Campus
Foresterhill Health Campus

Foresterhill Health Campus

The Foresterhill Health Campus is one of the largest clinical complexes in Europe which includes the Medical School, large teaching hospital, the Institute of Medical Sciences and the Rowett Institute.

Aberdeen Centre for Health Data Science

The Centre for Health Data Science is a partnership between the University of Aberdeen, NHS Grampian and NHS Research & Development North Node.

Find out more

Get in Touch

Contact Details

Address
Student Recruitment & Admissions
University of Aberdeen
University Office
Regent Walk
Aberdeen
AB24 3FX