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SECURITY AND PRIVACY FOR DATA SCIENCE

COMPSCI 763
Course Description

Security and privacy concerns in data science. Three core subjects will be considered: Differential privacy and algorithmic fairness; Adversarial machine learning; and Applied cryptography, especially with applications to machine learning. In addition, a selection of more advanced topics will be covered. Possible examples include additional notions of privacy, language-based security, robust optimization. A firm grasp of probability/statistics (STAT/​MATH  431) is recommended. Previous exposure to at least one of cryptography (COMP SCI/​E C E/​MATH  435), security (COMP SCI 642), and modern machine learning (COMP SCI/​E C E/​M E  539or540) is also recommended.

Prerequisties

Graduate/professional standing

Satisfies

This course does not satisfy any prerequisites.

Credits

Not Reported

Offered

Not Reported

Grade Point Average
3.73

3.78% from Historical

Completion Rate
95.45%

-2.16% from Historical

A Rate
77.27%

37.75% from Historical

Class Size
22

-19.51% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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