This course focuses on data preprocessing, feature engineering, and machine learning algorithms. In addition to covering popular supervised machine learning algorithms such as KNN, Linear and Logistic Regression, Naïve Bayes, Trees and Ensembles, and Support Vector Machines, the course provides practical insight into contemporary unsupervised learning techniques used for clustering and market basket analysis. Prerequisite: BSTAT 3321 and INSY 3300.