Bayes Centre

Health Data Science

This online credit-bearing course aims to equip healthcare professionals with the key foundations and data skills that are needed for data-driven innovation.

Course Summary

Data science is revolutionising how medicine is understood, how biomedical research is conducted and how healthcare is delivered. Despite the widely-recognised opportunities that data can bring to biomedicine and healthcare, there is a shortage of data skills in the healthcare sector. This course offered by the Usher Institute aims to equip healthcare professionals with the key foundations and data skills that are needed for data-driven innovation. It provides a gentle introduction to key concepts, principles and methods of data science in health, enabling you to explore the potential for data to transform healthcare. You will learn how to use current data science tools to process healthcare data for effective analysis and reporting and gain practical experience in working with data. You will also gain critical understandings of ethical and legal implications of working with healthcare data.

By the end of this course, you will be able to:

·       Explain and critically discuss key concepts, principles and methods of data science in health.

·       Apply a range of specialised data science techniques to different medical and healthcare scenarios.

·       Analyse health data with the use of the R programming language, including summarisation, visualisation and interpretation.

·       Critically examine the ethical, societal and regulatory principles and implications of data science in health.

Further information can be found in the University's course catalogue: 

Health Data Science

Course Delivery Information

This course is being offered twice in the 21/22 academic session

Start Dates: 11th April 2022
Course Duration: 10 weeks
Total Hours: 100 (Lecture Hours 10; Tutorial Hours 5; Independent Study and Assessment Hours 85)
Method of Assessment: Coursework 100%
Level:  This is an introductory Masters course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.

Course Fees and Funding

Course fees for 21/22 are £960, but Scottish Funding Council funding is available for people employed, unemployed or furloughed in Scotland (residency requirements apply). Full-time students are not eligible for funding. 

Funding and Eligibility 

Entry Requirements

As this course is designed mainly for health and care professionals, we expect our students to have qualifications or work experience in such environments (e.g. NHS National Services, Acute/Community/Public health), Third sector organisations, Social Services, Nursing homes, pharmaceutical companies, diagnostic laboratories, etc.). An understanding of the fundamentals of maths and statistics (at Higher level) would be advantageous but is not a prerequisite for joining the course.

You should be educated to a degree level as this course is catering for those seeking postgraduate academic credit. However, professionals who are involved with managing services and caseloads and have 5 years of work experience may also apply even if they do not hold a degree qualification.

Check whether your international qualifications meet our general entry requirements:

English Language Requirements

You must be comfortable studying and learning in English if it is not your first language.

 

Apply Now

Applications for April 2022 are now open.

In order to verify that you meet the entry requirements for this course, you will be required to provide either:

  • a degree certificate/transcript for your highest/most relevant academic qualification, or
  • a CV and reference from an employer (if employed) or professional associate (if unemployed) outlining your suitability for the course

The degree certificate/transcript or CV should be emailed to bayes-training@ed.ac.uk within 24 hours of submitting your application. References should be emailed to the same address (from an institutional/company account if from your employer) within 1 week of submitting your application. 

Once complete, your application will be processed in 1-2 weeks. Applications will be processed on a first come, first served basis with priority given to applicants who meet the criteria for a funded place. We aim to email all applicants within 2 weeks of submission regardless of the outcome of their application.

APPLY HERE

Applications will close on 27th March 2022.