Course summary

With an emphasis on skills training and theory content, this programme aims to produce self-reflective, critical-thinking postgraduates who are able to solve problems and enthusiastically tackle new challenges in biological data science, with particular relevance to academia, and the biotechnology and pharmaceutical industries. The programme will provide a thorough grounding in key areas of how we can access, manipulate and analyse big data and introduce students to some of the main approaches used for data analysis and interpretation, focussing on the different algorithms for machine learning, statistical analysis and data modelling. Students will gain skills in applying computational methods to analyse data, make predictions, and evaluate performance. The programme will also provide the skills a data scientist will need to program algorithms to manipulate and analyse data, by addressing current programming paradigms and languages that are commonly used for data science, with a focus on turning data into information. Students will enhance their critical skills in information retrieval, research ethics, entrepreneurship, statistics, analysis of current science and literature, as well as transferable skills in presentation and communication, data visualisation, team-working, problem solving, and project management. The programme will enable students to learn about and experience the world leading collection of technology platforms in the biosciences on offer at the University of Dundee or alternatively gain an understanding and practical knowledge of molecular modelling and simulation in the fields of biology and biopharma. Students will undertake a capstone quantitative biology research project, enabling them to refine their practical skills, interact with researchers at the forefront of their discipline. The programme, which has benefitted in its development from insights gained through extensive industry interactions, aims to equip students with the necessary skills and knowledge for a successful career in a variety of academic, industrial and science-related sectors related to data sciences in a biological or biomedical context.