MS6221 - Predictive Modeling in Marketing | ||||||||||||
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* The offering term is subject to change without prior notice | ||||||||||||
Course Aims | ||||||||||||
The
goal of the class is to provide a broad overview of modern data-driven
marketing techniques. We will cover the main areas of marketing that require
data-driven decisions — targeted promotions and advertisements, churn
management, recommender systems, pricing, and demand prediction. The emphasis
is on applied predictive modeling in python, and how machine learning tools are
employed in the data science industry. The prerequisites include one course in
probability and statistics and one course in regression analysis. Students are
expected to work at least 5 hours after every lecture. | ||||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||||
Continuous Assessment: 100% | ||||||||||||
Detailed Course Information | ||||||||||||
MS6221.pdf | ||||||||||||
Useful Links | ||||||||||||
Department of Management Sciences |