Health Data Science MSc

Health Data Science combines health research, mathematics, statistics and computing sciences to address health and care problems using data. Our MSc programme enables students from both healthcare and computational backgrounds to develop their health data science skills, supported by an interdisciplinary team of academics, NHS and industrial partners.<br/><br/>Nationally and internationally there is a critical shortage in data intensive analytic capacity applied to healthcare. The effective and efficient use of data has the potential to create the transformative step change needed through targeting health and care improvement. Our interdisciplinary MSc in Health Data Science aims to develop the next generation of health data scientists. The programme is delivered by academics from our Aberdeen Centre for Health Data Science (ACHDS). The Centre for Health Data Science aims are to create innovative, interdisciplinary, data science solutions to the big challenges for health and health care, to improve health for individuals, local communities and globally.<br/><br/>The programme offers a wide range of specialist elective options to allow students to build a personalised masters depending on their background, interests and skills and includes a work-based placement or research project. At the end of the programme students will be able to evaluate, critique and demonstrate competency in the practical application of current data intensive analytical methods and current health and care research methods. The MSc is ideally suited to healthcare professionals who wish to develop data health science skills or for students from computational and/or data intensive science backgrounds who wish to work in the health sector.<br/><br/>The programme is delivered via blended learning and will involve a variety of teaching methods including face to face lectures, tutorials, PowerPoint videos with accompanying self-tests and quizzes, video interviews with accompanying guides, computer-based practical sessions, self-study of recommended reading material and discussion boards. This mixed approach to teaching ensures that a range of different learning opportunities are provided for all students.