In today’s healthcare landscape, understanding which genomic factors influence disease risk and treatment response is paramount. Our module delves into the pivotal role of genomic data in deciphering disease aetiology and tailoring treatment plans to individuals, aligning with the ambition of healthcare providers globally to integrate genomics into patient care. Through a blend of theoretical teaching and hands-on exercises, you’ll gain proficiency in specialized statistical methods and programming necessary to navigate complex genomic datasets. From genotype quality control to polygenic risk scores, our comprehensive curriculum covers key analysis techniques essential for genomic research, including both traditional statistical techniques and machine learning methods. It assumes no prior knowledge of genomic data, with an introduction to the terminology and structure of the data, as well as to linux programming during the first two weeks. With a focus on practical application, and supplemented by guest lectures from leading experts, our module prepares you to be able to confidently analyse and interpret the huge and complex datasets that are typical within statistical genetics and pharmacogenomics research. Learning will be assessed via two practical assessments.