Algorithms for Data Science

CDS DS 320

  • Quantitative Reasoning II
  • Critical Thinking

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.

FALL 2023 Schedule

Section Instructor Location Schedule Notes
A1 Onak CGS 527 TR 1:30 pm-3:15 pm

FALL 2023 Schedule

Section Instructor Location Schedule Notes
A2 Onak CAS 220 M 3:35 pm-4:25 pm Class Full

FALL 2023 Schedule

Section Instructor Location Schedule Notes
A3 Onak CDS 263 M 4:40 pm-5:30 pm

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
A1 Goldner CAS 313 TR 2:00 pm-3:15 pm WebReg Restricted

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
A2 Goldner CDS 264 W 3:35 pm-4:25 pm WebReg Restricted
Class Full

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
A3 Goldner CDS 263 W 4:40 pm-5:30 pm WebReg Restricted

Note that this information may change at any time. Please visit the Student Link for the most up-to-date course information.