Predictive Analytics

(3 Credit Hours) · Undergraduate

Predictive analytics uses data, statistical modeling, and machine learning to forecast future outcomes and support better decisions. This course introduces the tools and techniques organizations use to turn large, complex datasets into actionable predictions. Students will learn how companies use data to anticipate customer behavior, manage risk, optimize operations, and gain competitive advantage, such as recommending products, predicting loan defaults, or identifying customer churn. Topics include data preparation, predictive modeling, classification and regression methods, model evaluation, and the practical use of machine learning algorithms. Emphasis is placed on applying analytics and computing tools to real business problems and interpreting results for decision-making. By the end of the course, students will understand how predictive models are built, validated, and deployed, and how analytics and AI techniques shape modern organizational strategy.