ISM 250: Stochastic Optimization in Information Systems and Technology
First in a sequence of courses in information systems and technology management (ISTM). Provides systematic methodology and corresponding set of methods and analytical tools to address the field of ISTM in an integrated manner; provides required training in stochastic optimization and other algorithmic approaches, such as dynamic programming, to achieve business intelligence in corporate enterprises. Students should have solid background in the following: probability equivalent to statistics, stochastic methods, calculus, linear algebra, mathematical maturity, stochastic processes, and optimization. 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
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