A technical analytics course. Covers supervised and unsupervised learning strategies, including regression, generalized linear models, regularization, dimension reduction methods, tree-based methods for classification, and clustering. Upper-level analytical methods shown in practice, e.g., advanced naive Bayes and neural networks. Cross-listed with CMDA 4654 and STAT 4654. (3H, 3C)
Prerequisite: CMDA 2006 or equivalent.