MS6221 - Predictive Modeling in Marketing | ||||||||||||
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| * The offering term is subject to change without prior notice | ||||||||||||
Course Aims | ||||||||||||
The goal of this class is to provide a comprehensive overview of modern data-driven marketing techniques. We will explore key areas of marketing that rely on data-driven decisions, including targeted promotions and advertisements, churn management, recommender systems, pricing, and demand prediction. The course will emphasize applied predictive modeling in Python and the use of machine learning tools in the data science industry. Prerequisites include one course in probability and statistics, and one course in regression analysis. Students should expect to dedicate at least five hours of work following each lecture. | ||||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||||
Continuous Assessment: 100% | ||||||||||||
Detailed Course Information | ||||||||||||
| MS6221.pdf | ||||||||||||
Useful Links | ||||||||||||
| Department of Management Sciences | ||||||||||||
