Winter 2023: Algorithms for Data Science
Winter 2023: Algorithms for Data Science
Course No:
EECS 498-005
Credit Hours:
4
Instructor:
Michal Derezinski
Prerequisites:
EECS 376, linear algebra and probability
This course will introduce algorithmic and theoretical aspects of data science. With the emergence of machine learning and data science, as well as the ever-increasing data sizes, providing theoretical foundations for these areas 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) will be still important, some topics will introduce new concepts and ideas, including randomized dimensionality reduction, sketching algorithms, and algorithms for continuous optimization.
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