This course is offered in two modes: either face to face (on-campus) and fully online.

Healthcare organisations have a vast amount of data: electronic medical records, claims, registries, medical images, and other types of digital health data. Machine learning techniques learn from previous experience in order to discover patterns and relationships in data, and have been found to perform extremely well in large datasets.

This course provides an introduction to machine learning techniques through a series of health applications.

Algorithms for supervised and unsupervised learning are covered, including linear regression and classification, tree-based methods, clustering, dimensionality reduction and neural networks.

Students will learn about the underlying supporting theory of these techniques, as well as gain the applied practical skills required to effectively apply these techniques to new health data problems.