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Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

Topic: Probability in Computer Science. Introduction to probability theory with applications to computer science. Topics include conditional probability, independence, Bayes theorem, random variables, joint and conditional distributions, expectation, variance and covariance, central limit theorem, law of large numbers, Markov chains, entropy, maximum likelihood estimation, Bayes estimation, linear regression, principal component analysis, hypothesis testing, and confidence intervals. Prerequisite: Math 241. NOTE: students taking this course in the CS curriculum in the College of Engineering will not need to take Math 461 or Math 463, but this course will not count as a 400-level CS technical elective.