CMPSC 291A Intro to Differential Privacy: Theory, Algorithms and Applications
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.