Units: 4
Hours: Lecture, 3 hours; activity, 3 hours
Catalog page 462
Prerequisites: MGT 201, MGT 209, MGT 251A; graduate standing; or consent of instructor
Description: Teaches to use data for strategic marketing decisions. Will learn to apply Python and R to analyze complex marketing datasets, performing advanced statistical and machine learning techniques. Key topics include sales forecasting, churn prediction, A/B testing, and customer lifetime value (CLV). Complete capstone project using real-world case studies.