This course provides an introduction to the world of machine learning. By the end of this course students will have a sound understanding of the key concepts of machine learning, analyze data using some of its main methods, and a solid foundation for more advanced or more specialized study. The course covers standard topics in supervised and unsupervised learning, including the most common learning algorithms for regression, classification and clustering, but also touches on advanced topics in machine learning particularly important for public policy, such as uncertainty quantification. Students will learn the fundamental concepts underlying machine learning algorithms as well as the practical use of machine learning algorithms using open-source frameworks.
