Machine Learning

Catalog description

An in-depth investigation of the theories, methods, and techniques of various machine learning models. Topics include how artificial intelligence differs from programming; supervised and unsupervised learning models and techniques; validation strategies; data preparation and imputation; organizational, ethical and leadership applications and challenges.