This course explores the principles, methods, and applications of machine learning (ML) and predictive analytics within the context of modern business environments. Designed for business and data-driven professionals, the course bridges the gap between complex machine learning algorithms and their strategic value across functions such as marketing, finance, operations, human resources, and customer experience. Students will learn to frame business problems as machine learning tasks, select and apply appropriate modeling techniques, and interpret predictive outputs to guide data-informed decision-making. Core topics include supervised and unsupervised learning, feature engineering, and model evaluation. Prerequisite(s): MSAI 300 and MSAI 301.