University of Birmingham - College of Medicine and Health
MSc in Health Data ScienceBirmingham, United Kingdom
DURATION
1 up to 2 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
Request application deadline *
EARLIEST START DATE
Sep 2025
TUITION FEES
GBP 32,510 / per year **
STUDY FORMAT
On-Campus
* international students: may 12 | UK students: august 29
** international: £32,510 | UK full-time: £10,900 | UK part-time: £5,450
Key Summary
Introduction
Course overview
This unique programme provides a blend of theoretical knowledge and practical experience, preparing graduates for impactful careers in the rapidly growing field of health data science. We will equip you with skills in AI, health data and advanced computing required to shape the future of the clinical and biomedical worlds.
Learn about the breadth of health data science and AI. Our programme explores everything from medicine, biology, and healthcare systems to ethics, clinical practice, machine learning, mathematical modelling, and computer science.
Throughout our course, you’ll also gain hands-on experience tackling real-world data analytics problems and developing practical solutions.
Course highlights
This programme takes you into the fascinating world of cutting-edge technology, health data, and the limitless potential of artificial intelligence. We’ll teach you how to design, perform, and enhance analyses using the latest methods and technologies to address practical medical and clinical questions.
You'll learn about the breadth of health data science and its applications. We'll teach you how to design, perform and enhance analyses with the appropriate methods and technologies to address practical medical and clinical questions.
In addition, you'll receive comprehensive training in clinical bioinformatics, health informatics, epidemiology, clinical systems, integrated multimodal data analysis, and omics analytics. Our approach ensures you gain the skills needed to innovate and excel in the evolving landscape of health data science.
- Develop Computational Expertise: Acquire essential computational techniques for analysing health data, with no prior computing experience required.
- Explore Healthcare Systems: Gain in-depth knowledge of healthcare systems, including their operational structures, ethical considerations, and governance frameworks.
- Harness Transformative Potential: Discover how health data science can revolutionise healthcare by leveraging patient-specific information, such as electronic health records and genomics, to drive advancements in research, clinical care, and innovation.
Gallery
Admissions
Scholarships and Funding
To help you afford your studies, we’ve put more than £33 million into student support and scholarships. We also offer a range of advice on searching for funding and managing your finances.
Birmingham Masters Scholarships
We want to welcome the brightest talent to our postgraduate community. That’s why our Birmingham Masters Scholarships award £3,000 to more than 300 students each year.
Curriculum
Course Structure
This course will run over 12 months in a full-time-mode. While the exact content may change, here’s what you can expect to study each term.
First Term
In the first term, teaching will focus on the fundamentals required to perform Heath Data Science. This includes the basics of programming, data manipulation, statistical and mathematical analyses as well as the fundamental machine learning approaches employed in AI.
Second Term
In the second term, you'll focus on more advances research methods and data types. The teaching will focus on epidemiology, image, genetic information and other unstructured data. You'll also learn about the underlying ethics and governance guiding research in the Health Data Science field.
Dissertation
The programme concludes with a three-month individual dissertation project. Within the project you'll dive deep into a particular health data challenge of your choice and present your research findings.
Module information
The course comprises 120 credits of taught material. There is also a 60 credit research project.
The modules listed below are an indication only and may be subject to change. Occasionally, it may be necessary to make changes to modules, for example, to ensure they remain current and relevant.
The following must be taken:
- Data Analytics and Statistical Machine Learning for Health Data Science
- Epidemiology and Health Informatics
- Essentials of Mathematics, Statistics and Programming
- Foundations of Computing Practices in Health Data Science
- Health Data Fundamentals
- Integrative Multimodal Data Analytics
Students must either take the 60 credit module, or both the 40 and 20 credit modules
- Health Data Analytics
- Health Data Science Challenges
- Interdisciplinary Health Data Research Project
Program Tuition Fee
Career Opportunities
The demand for health data scientists is skyrocketing. Prepare yourself for an exciting career in either industry or academia where artificial intelligence, clinical sciences and biomedicine intersect.
Careers Network
Get ready for tomorrow, with advice, guidance and opportunities at every step of your studies. From developing new skills to preparing for a PhD, our Careers Network can help you gain an advantage in the job market or advance in your field.
Whatever you plan to do after your degree, the Careers Network offers a range of events and support services including networking opportunities, career coaching, one-to-one guidance, careers fairs and links with leading graduate recruiters. We also offer subject-specific careers consultants and a dedicated careers website for international students.
Faculty
Program delivery
Course delivery
This programme is available at our Edgbaston and Dubai campuses. You’ll learn from world-leading academics and researchers at a top 100 UK university. From the outset we’ll challenge and encourage you to become an independent and self-motivated learner.
This course consists of six taught modules and a dissertation.
- Taught modules – Each module represents a total of 200 hours of study time, including preparatory reading, self-guided study and assignment preparation.
- Assessments – these include essays, exams, oral presentations, and computer-based problem-solving exercises.