ISM 251: Information Systems and Technology Management 2
Provides a systematic methodology and corresponding set of methods and analytical tools in stochastic and neuro-dynamic programming used for business intelligence in corporate enterprises and A1 and Machine learning research and applications in computer science, computer engineering, and electrical engineering and related to applied mathematics and statistics, business, management, and economics. Students should have solid background in probability equivalent to statistics, stochastic methods, calculus, mathematical maturity, stochastic processes and optimization, business intelligence and algorithms. Prerequisite(s): Computer Engineering 107 or Applied Mathmatics and Statistics 131 or permission of instructor. Enrollment restricted to graduate students. Applied Mathematics and Statistics 205B, 230, and course 250 recommended. R. Akella
5 Credits
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