Data-Driven Modeling and Learning. 3 credits

Catalog description

Focuses on advances in data science related to statistical learning theory by introducing modern topics on data analytics, classification, clustering, and regression techniques, as well as data-driven decision-making. The course includes the statistical and optimization background essential for developing new efficient statistical learning, data-driven methods and algorithms. Also discusses applications of data-driven statistical learning algorithms to the solution of important real-world problems that arise in areas of science and other domains. Offered by Computational & Data Sciences . May not be repeated for credit.