COURSE CURRICULUM

The Population Health Data Science MSc combines rigorous training in statistical analysis, computational methods, and health research to prepare students for careers as data scientists in the healthcare sector. The program covers fundamental concepts in medical statistics and the foundations of health data science, providing a strong quantitative base for analyzing complex health datasets. Students develop expertise in statistical modelling, computationally intensive methods, and advanced statistical techniques, with options tailored for both full-time and part-time study. The curriculum emphasizes the practical application of statistical methods to real-world health challenges, including the analysis of epidemiological data and the interpretation of large-scale health datasets. Core modules such as statistical computing and inference, epidemiology, and further topics in health data science ensure students gain both theoretical knowledge and hands-on skills using key software and programming tools. The course also strengthens critical thinking, research design, and problem-solving abilities, enabling students to translate data insights into meaningful conclusions for public health and clinical decision-making. Graduates leave the program equipped to work in hospitals, research institutions, public health organizations, and policy-making bodies, using evidence-based, data-driven approaches to address contemporary population health challenges and contribute to informed healthcare decision-making.