500

13-510 Mathematics for Data Scientists

Differentiation and integration of functions; basic matrix operations; linearization; linear and nonlinear optimization techniques; clustering and similarity measures, introduction to probability and statistics, basic computational algorithms. Includes frequent illustration of concepts using mathematical computation tools.

3

13-511 Concepts of Statistics I

Distribution of random variables, conditional probability and independence, distributions of functions of random variables, limiting distributions.

3

Prerequisites

13-510.

13-512 Concepts of Statistics II

Point estimation, sufficient statistics, completeness, exponential family, maximum likelihood estimators, statistical hypotheses, beta tests, likelihood ratio tests, noncentral distributions.

3

Prerequisites

13-511.