This course equips students with the core mathematical tools needed to design, analyze, and implement data science algorithms. Topics are carefully selected to support the computational, statistical, and analytical foundations of modern algorithmic methods. Key focus areas include linear algebra, discrete mathematics, matrix decompositions, optimization theory, and computational complexity. Through hands-on modeling and problem-solving, students will explore real-world applications, uncover algorithmic insights using matrix and graph theory, and build strong mathematical intuition for data-driven problem solving.