Algorithms for Data Science

An algorithms course grounding classical design methods, including greedy strategies, divide and conquer, and dynamic programming, in data science applications. Students then study methods suited to large or streaming datasets, where repeated scans are infeasible, practicing with approximation and randomized algorithms designed for efficiency at scale.