Algorithms for Data Science

Enrollment Requirements: Undergraduate Prerequisite: (CDSDS 121 or CASCS 132 or CASMA 242 or ENGEK 102 or ENGEK 103) and (CDSDS 110 or CASCS 111 or ENGEK 125 or (ENGEK 121 and ENGEK 122)) - Grade of C or higher required in all courses This course covers the fundamental principles underlying the design and analysis of algorithms. We will walk through classical design methods, such as greedy algorithms, design and conquer, and dynamic programming, focusing on applications in data science. We will also study algorithmic methods more specific to data science and machine learning. The course places a particular emphasis on algorithmic efficiency, crucial with large and/or streaming data sets, for which multiple scans of data are infeasible, including the use of approximation and randomized algorithms. Effective Spring 2022, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Critical Thinking.