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

Please note that prior to Fall 2011, the Technology & Information Management department was known as Information Systems Management.  For classes prior to Fall 2011, please see the ISM schedule page.



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 may enroll if they have completed Computer Engineering 107 or Applied Mathematics or Statistics 131 or have permission of instructor. Applied Mathematics or Statistics 205A and Computer Engineering 230 are recommended. R. Akella

5 Credits

  • Section 01
    James G Shanahan (jgshanah)
    Telecast to SV
  • Section 50
    James G Shanahan (jgshanah)
    Telecast to SV

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