Computer System Modeling Fundamentals
COM SCI XLC 112
This course is part of the UCLA Henry Samueli School of Engineering and Applied Science (HSSEAS) Master of Science in Engineering Online (MSOL) program. It is available only to students pre-approved by HSSEAS. See below for more information.
About this course:
Requisite: Statistics 100A or 110A. Probability and stochastic process models as applied in computer science. Basic methodological tools include random variables, conditional probability, expectation and higher moments, Bayes theorem, Markov chains. Applications include probabilistic algorithms, evidential reasoning, analysis of algorithms and data structures, reliability, communication protocol and queuing models.