Prerequisite: Admitted to MS in Data Science and Analytics program.

This foundational course covers essential mathematics for studying data science and analytics, centering on calculus, linear algebra, and multivariate calculus. Key topics include limits and continuity, applications of derivatives and integrals, multivariate differentiation and integration, and matrix algebra including eigenvalues. To support learning, students engage in practical applications using statistical software such as R or Python, with no prior programming experience required. By the end of the course, students will have enhanced their mathematical skills enabling them to apply these concepts across data science and analytics coursework.