Privacy-Preserving Data Analysis Seminar

CMPSC 591 - Spring 2027 - Allegheny College

How do Apple, Google, and the US Census Bureau extract valuable insights from massive datasets without exposing personal information? In this 2-credit group independent study, we’ll explore frameworks like differential privacy that allow us to learn useful information while mathematically guaranteeing individual privacy. Students will study the algorithmic mechanisms behind these protections and how modern computer scientists balance rigorous privacy requirements with the demand for accurate data analysis.

In this course, we will explore the following topics:

Notions of data privacy
Differential privacy and its applications
Deployments of differential privacy in industry and government
Building a privacy-preserving data analysis pipeline

What we’ll be doing in this course:

Reading and discussing a fun and approachable book on data privacy
Working on a project employing privacy-preserving techniques
Learning fundamentals of research in computer and information science

If you’re interested in taking this course, please fill out the interest form. You’ll need permission from the instructor to enroll in this course.

Course Info

Prerequisite: CMPSC 101, CMPSC 105, or equivalent experience with programming and data analysis
Meeting Time: W 2:30-4:00 PM, Alden 109

Readings

We will read the book Differential Privacy from the MIT Press Essential Knowledge series. This book is available open access online through the MIT Press website or for just under $20 in paperback.