Contents:
(1) Linear algebra: orthogonalization, symmetric matrices, quadratic forms, matrix decompositions and applications to data analysis.
(2) Multivariable calculus.
(3) Optimization and Linear Programming and applications to data analysis.

Formative Objectives:
- To provide students with adequate mathematical foundations of linear algebra, multivariable calculus, and optimization.
- To give students quantitative tools, whose employment in data science is shown through different examples and case studies.