Machine Learning

Catalog description

This course provides an introduction to machine learning with the opportunity to develop and implement data-driven solutions and predictive models for different applications. Topics broadly include: (i) supervised learning, (ii) unsupervised learning, (iii) dimensionality reduction and feature selection techniques, and (iv) best practices and model evaluation methods in machine learning. The course will also draw examples from numerous case studies and applications.