Fall 2022 Course Descriptions

CS 151-02 Privacy, Security, and Data

J. Bater
MW 6:00p-7:15p, Joyce Cummings Center 260
M+ Block

Organizations today collect and analyze massive amounts of information for important decision-making applications. However, these large-scale analytics often compromise sensitive user information, such as medical or financial records. In this course, we will survey and apply state of the art techniques in privacy-preserving data science, such as differential privacy and secure multi-party computation, to learn how to build systems that provide useful results while still respecting user privacy. Students will be expected to read research papers, give in-class presentations, and complete a final project utilizing real-world data.

Prerequisite: CS 115-level knowledge; some experience with Python, C++, and basic probability.

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