TIM250: Stochastic Optimization in Business Intelligence: Digital Advertising and Online Marketing

Trains students in stochastic optimization and other algorithmic approaches, such as stochastic dynamic programming, to achieve business intelligence (BI) optimization. Special emphasis on digital advertising, and online and computational marketing. Students should have solid background in: probability equivalent to statistics, stochastic methods, calculus, liner algebra, mathematical maturity, stochastic processes, and optimization. First of a sequence of courses in information systems and technology management (ISTM). Provides students with systematic methodology and corresponding set of methods and analytical tools to address the field of ISTM in an integrated manner.(Formerly Stochastic Optimization in Information Systems and Technology) Enrollment restricted to graduate students; undergraduates who have completed Computer Engineering (CMPE) 107 or Applied Mathematics & Statistics (AMS) 131 may enroll by permission of instructor. AMS 205A, CMPE 230 recommended.

5 credits

Year	Fall	Winter	Spring	Summer

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