DASC 6000 - Data Science Methods I

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First of a two-course sequence. P: Enrolled in the master of science in data science program or consent of instructor. Essential mathematical, statistical, and computational knowledge needed for data scientists. Review of set theory, permutations and combinations, sums, functions, relations, recurrences, essence of differentiation and integration, elementary graph theory, and essential linear algebra. Other topics include conditional and joint probability, random variables and their distributions, expectation and moments, transformations and conditional expectation, inequalities and limit theorems, Markov Chains and Markov Chain Monte Carlo, and Poisson processes.