This course provides a rigorous mathematical foundation for the statistical and algorithmic reasoning involved in modern data science. It is designed to prepare students to approach data modeling, simulation, and evaluation with mathematical precision and clarity. Students will explore logic, set theory, combinatorics, linear models from first principles, and essential probability theory with a computational focus. Emphasis is placed on the conceptual structure behind methods such as regression, classification, and clustering, enabling students to understand not only how to use them—but why they work.