ISM250: Stochastic Optimization in Business Intelligence: Digital Advertising and Online Marketing

Please note that after Summer 2011, the Information Systems Management department was renamed Technology & Information Management.  For classes after Summer 2011, please see the TIM 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

YearFallWinterSpringSummer
2010-11
  • Section 01
    James G Shanahan (jgshanah)
    Telecast to SVC
  • Section 50
    James G Shanahan (jgshanah)
    SVC Telecast
2008-09
  • Section 01
    Ramakrishna Akella (rakella)
    Telecast to SVC
2007-08
  • Section 01
    Ramakrishna Akella (rakella)
    Telecast
2005-06

While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.