find your perfect postgrad program
Search our Database of 30,000 Courses
University of Cambridge: Healthcare Data Science
| Institution | University of Cambridge |
|---|---|
| Department | Professional and Continuing Education |
| Web | https://www.cam.ac.uk |
| Study type | Taught |
Summary
The MSt in Healthcare Data Science course is designed to empower learners by integrating scientific principles with a comprehensive range of behavioural, managerial, and technical skills. The goal is to cultivate highly competitive professionals capable of playing effective roles in health data science projects. The design of the course considers the multidisciplinary nature of this field and incorporates required components from mathematics, statistics, computation, and health sciences to reflect the skills required for level 7 as well as incorporation of knowledge and skills outlined by industry.
The MSt in Healthcare Data Science is designed for professionals and aspiring leaders who want to advance their careers at the interface of health and data science. It is particularly suitable for:
-
healthcare professionals (e.g. clinicians, nurses, allied health staff, public health practitioners) who would like to enhance their technical, coding and data science skills to develop and apply data-driven approaches to improve patient care and healthcare systems
-
data scientists, statisticians, and computational scientists seeking to specialise in healthcare applications and gain a deeper understanding of the medical, behavioural, and organisational contexts in which their work will be applied
-
researchers and academics in medicine, biomedical sciences, or related fields who want to strengthen their quantitative and technical skills for health research
-
policy makers, managers, and professionals in health organisations who require a robust understanding of health data analytics to inform evidence-based decisions, design interventions, and manage health services
-
industry professionals (e.g., in biotechnology, pharmaceuticals, digital health, or medtech) who are looking to bridge scientific, technical, and healthcare knowledge to develop and deliver innovative solutions
This course will appeal to individuals who are:
-
motivated to combine mathematical, statistical, computational, and health sciences in a multidisciplinary way
-
eager to develop both technical expertise and leadership skills to contribute effectively to data science projects in health
-
working professionals seeking a flexible, part-time programme that can fit alongside their careers
-
committed to advancing their impact in healthcare through innovation, evidence, and collaboration
The course will:
-
provide teaching and learning opportunities to gain the knowledge and skills that underpin and are at the forefront of the successful implementation of an advanced health-focused data science project
-
equip learners with current data science tools and techniques to manage and analyse large datasets across healthcare systems
-
advance learners’ programming and analytical skills for performing meaningful and reproducible analysis
-
develop, create and upskill healthcare data experts with the necessary expertise, and originality of application, to pursue and expand their roles in the context of the rapidly evolving environment of electronic health data
-
promote a comprehensive understanding of the practical and ethical considerations relevant to health data, informatics and innovation
-
provide work-relevant learning opportunities and practical expertise in the context of a critical awareness of current problems, best-practice, challenges, and potential solutions in the use of health data
-
provide students with advanced knowledge and skills required for design and execution of the health data science project capturing: the entire process from initial curiosity driven database queries, through to data analysis, statistical inference and visualization in an impactful and reproducible output
The programme provides the advanced skills and knowledge required to work and play an effective role in a rigorous health-focused data science project.
MSt
| Level | RQF Level 7 |
|---|---|
| Entry requirements | Typically, we expect a good UK undergraduate degree, such as a 2.1, or international equivalent. It is preferred that an applicant's first degree be in a subject relevant, or related to, life sciences, medical sciences, computational or data science. If your degree is not from the UK, check international qualifications on the University’s postgraduate site to find the equivalent in your country. |
| Location | Cambridge University The Old Schools Trinity Lane Cambridge CB2 1TN |
Fees
| England | 20592 GBP for Whole course |
|---|---|
| Northern Ireland | 20592 GBP for Whole course |
| Scotland | 20592 GBP for Whole course |
| Wales | 20592 GBP for Whole course |
| International | 41184 GBP for Whole course |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | Typically, we expect a good UK undergraduate degree, such as a 2.1, or international equivalent. It is preferred that an applicant's first degree be in a subject relevant, or related to, life sciences, medical sciences, computational or data science. If your degree is not from the UK, check international qualifications on the University’s postgraduate site to find the equivalent in your country. |
| Location | Cambridge University The Old Schools Trinity Lane Cambridge CB2 1TN |
Fees
| England | 20592 GBP for Whole course |
|---|---|
| Northern Ireland | 20592 GBP for Whole course |
| Scotland | 20592 GBP for Whole course |
| Wales | 20592 GBP for Whole course |
| International | 41184 GBP for Whole course |
Not what you are looking for?
Browse other courses in Data analysis, Health informatics or Health science, or search our comprehensive database of postgrad programs.Postgraduate Bursary Opportunity with Postgrad.com
Are you studying as a PG student at the moment or have you recently been accepted on a postgraduate program? Apply now for one of our £2000 PGS bursaries.
Click here