Applied Machine Learning for Biological Data

This course introduces the application of machine learning methods to biological and genomic data using Python (Module 1 gives you an overview of the Python workflow you need to know). The materials cover core concepts such as data handling, classification, regression, clustering, and deep learning, combining theoretical foundations with hands-on coding exercises on real-world datasets. Participants will work with widely used tools including NumPy, Pandas, and PyTorch while exploring reproducible workflows and modern computational approaches such as containerisation and GPU-accelerated analysis. The course is aimed at researchers and data analysts who want to apply machine learning techniques to biological research questions and large-scale genomics data.