Belfast | Exeter | Birmingham | Sheffield | York
Our MSc Health Data Science course aims to create a new breed of scientist who can understand the healthcare sector and medicine, how data is collected and analysed, and how this can be communicated to influence various stakeholders.
The current model of healthcare delivery in the UK is subject to unprecedented challenges. An ageing population, the impact of lifestyle factors and increasing costs mean that the existing approaches may become unsustainable.
This, coupled with a drive towards personalised medicine, presents an opportunity for a step change in healthcare delivery.
To do this, we need to make best use of the health data we collect and create a better understanding of the relationship between treatments, outcomes, patients and costs.
This MSc promotes the need for translational thinking to provide the knowledge, skills and understanding that will be applied across new challenges within healthcare delivery.
Students from a variety of professional backgrounds will benefit from the course, as the structure of the MSc ensures that you will share this knowledge with each other and learn to work in multidisciplinary teams, rather than in specialist silos.
The course has eight taught units covering key skills for health data science. Seven units are core and there is one optional unit depending on training needs and background. For those studying for an MSc, there is also a 60-credit research project.
This course will allow you to:
Research project options
MSc students will have an opportunity to conduct their research project in other settings such as the NHS and the biopharmaceutical industry, as well as academia.
The course covers four main areas that bring together technical, modelling and contextual skills to apply these to real world problems when harnessing the potential of health data.
In each of the units that deliver the key skills, both the importance of the patient and the governance surrounding working in the healthcare environment (especially structures around information governance) is embedded throughout.
Each unit will use case studies provided by existing work and research at the Health eResearch Centre(HeRC). The course will focus on large and complex health datasets (often routinely collected) in environments that safeguard patient confidentiality.
The course will encourage intellectual curiosity, creativity, and critical thinking, providing transferable skills for lifelong learning and research and cultivation of reflective practice.
Through the development of these innovation, critical, evaluative, analytical, technical, problem solving and professional skills, you will be able to conduct impactful work and advance healthcare delivery.
We see learning and teaching as collaborative knowledge construction, which recognises the contribution of all stakeholders (academic staff, service users and carers and students). This is demonstrated in the course through contributions made by these stakeholders through case studies, examples, invited seminars and participation in group work.
A variety of teaching methods will be used within the constraints of the method of delivery. The course will be student centred and will be delivered from the outset using a combination of face-to-face, distance learning and blended learning units.
A range of assessments are used within each course unit and across the course as a whole.
All assessments require you to integrate knowledge and understanding, and to apply this to case studies and the outcomes of each unit.
Assessment will occur in a variety of forms including (but not exclusively) essays, case studies, assessed seminar/tutorial presentations and literature reviews.
Written assignments and presentations have a formative role in providing feedback (particularly in the early stages of course units) as well as contributing to summative assessment.
Online quizzes provide a useful method of regular testing, ensuring that you actively engage with the taught material.
The assessment of tutorials contains an element of self and peer evaluation, so you can learn the skills associated with the effective management of and participation in collaborative activity.
The course also places an emphasis on group work, as this a vital skill for professionals operating in a multidisciplinary area such as health data science, and this is shown in the teaching methods and assignments.
Each unit has a different emphasis on the group work assessment based on the nature of the material being covered, how they are to apply the knowledge and the work they are to complete.
The dissertation for the MSc requires you to undertake an extended written piece of work (10,000 to 15,000 words) that focuses on a specific aspect of health data science.
Visit the Health Data Science (MSc/PGDip/PGCert) page on the University of Manchester website for more details!
Never miss a course
Enter our scholarship competition
Get funding news, tips and advice
Hear about upcoming events
Get postgraduate loan updates
Hear about funded courses
Enter our scholarship competition
Discover international opportunities
We've been helping students find the right postgraduate course for over a decade.
We'll make sure you're the first to hear about scholarship opportunities and funding news.