15 780 - Stochastic Models in Business Analytics

Description
Prereq: 6.041B, 15.0791, or permission of instructor. Introduces core concepts in data-driven stochastic modeling that inform and optimize business decisions under uncertainty. Covers stochastic models and frameworks, such as queuing theory, time series forecasting, network models, dynamic programming, and stochastic optimization. Draws on real-world applications, with several examples from retail, healthcare, logistics, supply chain, social and online networks, and sports analytics.
Credits
12
Recent Professors
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Recent Semesters
Fall 2019
Offered
MW, F
Avg. Sections
2