Handbook

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

Healthcare organizations generate vast amounts of digital health data, including electronic medical records, claims, registries, medical images, and other types of data. Machine learning techniques are a set of methods that enable computers to learn from this data and identify patterns and relationships within it. These techniques are particularly effective when dealing with large datasets.

This course provides an introduction to machine learning techniques through various health applications. It covers algorithms for both supervised and unsupervised learning, including linear models, tree-based methods, clustering, dimensionality reduction, and neural networks. Students will not only learn the theoretical foundations of these techniques but also gain practical skills required to apply them effectively to new health data problems.