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PU5058: INTRODUCTION TO HEALTH DATA SCIENCE (2021-2022)

Last modified: 20 Oct 2021 11:30


Course Overview

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.

Course Details

Study Type Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Dimitra Blana

What courses & programmes must have been taken before this course?

  • Any Postgraduate Programme

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

This introductory course will give students from a variety of backgrounds a firm understanding of data science and its application to the health domain. The course will cover how data science is used to address healthcare problems; the role of health data scientists in research and healthcare; current challenges in the field; and the data science workflow using SQL and R (no coding experience is required).


In light of Covid-19 this information is indicative and may be subject to change.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

  • 1 Computer Practical during University weeks 11 - 16
  • 1 Seminar during University weeks 9 - 10, 17 - 19

More Information about Week Numbers


In light of Covid-19 and the move to blended learning delivery the assessment information advertised for second half-session courses may be subject to change. All updates for second-half session courses will be actioned in advance of the second half-session teaching starting. Please check back regularly for updates.

Summative Assessments

Design Project: Group

Assessment Type Summative Weighting 30
Assessment Weeks 20 Feedback Weeks 23

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Feedback

Students will be asked to design, produce and present to their tutors and peers a resource for the general public to discuss one of the current challenges in health data science. The resource could be a slide show, an infographic, a cartoon, etc.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualAnalyseAnalyse current challenges in health data science
ConceptualUnderstandDiscuss the role of health data scientists in research and healthcare
ProceduralUnderstandExplain how data science is used to address healthcare problems

Report: Individual

Assessment Type Summative Weighting 70
Assessment Weeks 16 Feedback Weeks 19

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Feedback

A report describing the application of the health data science workflow to address an example healthcare problem

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualEvaluateDiscuss the limitations and assumptions made in health data science projects
ProceduralApplyApply the data science workflow using R to healthcare problems

Formative Assessment

There are no assessments for this course.

Resit Assessments

Report: Individual

Assessment Type Summative Weighting 100
Assessment Weeks 25 Feedback Weeks 28

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Feedback

A report that discusses one of the current challenges in health data science, and describes the application of the health data science workflow to address an example healthcare problem

Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ProceduralUnderstandExplain how data science is used to address healthcare problems
ConceptualAnalyseAnalyse current challenges in health data science
ConceptualEvaluateDiscuss the limitations and assumptions made in health data science projects
ProceduralApplyApply the data science workflow using R to healthcare problems
ConceptualUnderstandDiscuss the role of health data scientists in research and healthcare

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