Winter 2022: Algorithms for Data Science

Winter 2022: Algorithms for Data Science

Course No:
EECS 498-004
Credit Hours:
4 credits
Instructor:
Euiwoong Lee
Prerequisites:
EECS 376 and linear algebra

This course will introduce algorithmic and theoretical aspects of data science. With the emergence of machine learning and data science, providing theoretical foundations for them will become increasingly important. The course will cover several important algorithms in data science and see how their performances can be analyzed. While fundamental ideas covered in EECS 376 (e.g., design and analysis of algorithms, NP-hardness, etc.) will be important, some topics will introduce new concepts and ideas, including sublinear time algorithms, algorithms for continuous domains, and average-case analysis.

More info (pdf)