Health Data Science, _MSc

15 Credit Points

We live in a time of ‘Big Data’ with the rapid growth in the digital capture of health information. Health Informatics is the science of data capture, linkage and analysis of large datasets to improve health. The demand for health researchers with training and experience in health informatics is high. For people practicing in Public Health, it is a key skill. It will equip students for any career in health research or public health practice and this course is an excellent stepping stone for those wishing to develop a specialist interest in the field.

15 Credit Points

Machine learning has the potential to revolutionise healthcare. The aim of this course is to introduce machine learning for health data science with examples of real-life healthcare applications, using the popular data science language R.

15 Credit Points

Data Science is an interdisciplinary field that seeks to identify and understand phenomena captured in structured or unstructured data, extract insights, and add value by generating predictions that aid optimization of processes and equipment. These techniques show considerable promise for bringing about a revolution, increasing the significance and value of owning and collecting data of all types. This course introduces the common techniques and considers the implications for data managers.

15 Credit Points

This course will equip students with the relevant skills to interpret and conduct systematic reviews on the effectiveness of healthcare interventions. Using lectures and practical sessions, students will understand the principles of systematic reviewing and the differences between narrative and systematic reviews. They will learn to formulate a clear research question and undertake each stage of systematic reviewing of randomised controlled trials. They will also learn about the importance of the levels of evidence and systematic reviews of other different study designs. This course will also introduce the students to advances in systematic reviews such as network meta-analysis and use of Individual Patient Data (IPD)

15 Credit Points

This work-based placement elective offers a professional placement with a government/public, industrial, civic or voluntary health and/or development sector organisation. You will undertake a ten-week placement with your host organisation, either within the organisation, remotely from Aberdeen, or using a combination of both. Placements are subject to availability and may be offered on a competitive basis.

15 Credit Points

The course aims to instill knowledge but, much more importantly, stimulate students’ thinking about the major challenges within different health systems and the options for the health services management. Furthermore, it aims to take a genuinely international perspective on health care, providing knowledge of different health care systems and encouraging comparison and critique. It covers a wide variety of topics including an overview of the health systems around the world, the effects of social inequalities on health inequalities and their repercussions for social policy and issues of public health policy towards tobacco, alcohol and obesity.

15 Credit Points

This course intends to develop a student’s statistical skills and understanding so that they can apply common multivariate regression modelling techniques to a range of health research data. The course will focus on the application, interpretation and communication of common regression models, including general linear models, log-linear models, logistic regression, and survival analysis. It assumes that students will already have completed a first course in statistics and have an understanding of bivariate techniques and basic mathematical skills.

60 Credit Points

This course offers students the opportunity to complete a substantial piece of data-driven, empirical work within their field of study under the supervision of an experienced researcher.

Topics available will be varied but within the domain of their field of study. Alongside supervisors, students will identify a suitable topic area, describe an appropriate study design and implement an empirical study to be completed within a laboratory setting. Students will be involved alongside the supervisors in the process of defining the research question, and developing the research plan and, where appropriate, obtaining regulatory approvals. This course is for non-laboratory based projects (if you are intending to undertake a project in a scientific laboratory setting you should register on MB5913)

30 Credit Points

This work-based placement elective offers a professional placement with a civic, government, industrial, public, research or voluntary health and/or development sector organisation. You will undertake a ten-week placement with your host organisation, either within the organisation, remotely from Aberdeen, or using a combination of both. Placements are subject to availability and are offered on a best match basis.