Data-driven Decision Modeling
4:10pm–5:25pm
Seeley W. Mudd Building 303
Morningside
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Introduction to modeling, estimating, and solving decision-making problems in the context of artificial intelligence and analytics. Potential topics include choice models, quantity models, online learning using multi-armed bandits, dynamic decision modeling, dynamic games, and Bayesian learning theory. Practice both theory and applications using Python programming
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Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
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