Covers fundamental principles of algorithm design and analysis (greedy algorithms, divide and conquer, dynamic programming) with applications in data science, plus algorithmic methods specific to data science and machine learning, emphasizing efficiency for large or streaming datasets via approximation and randomized algorithms.

Level

intermediate

Department

CDS

Credits

4

Prerequisites

DS 121 & DS 210