Quarter
Fall 2021
Instructor/s
Course Type
Special Topics Course
Course Area
Applications
Enrollment Code
62489
Location
Phelps 3526
Units
4
Day and Time
M/W 1 - 2:50 pm
Course Description

The graduate-level course covers the fundamentals of differential privacy (DP), as well as various applications of DP in statistical and machine learning applications.  Students will learn the fundamentals of DP and practice how to prove formal differential privacy guarantees. There will also be hands-on training on using “autodp” for state-of-the-art DP computation. The targeted audience of the course is graduate students in doing research in theory / algorithms, those doing applied research involving sensitive data (e.g., human subject data), as well as advanced undergraduate students with proper mathematical backgrounds.