CIS 6261
Trustworthy Machine Learning
Explores research at the intersection of machine learning and security and privacy. Topics include: adversarial machine learning; differential privacy; membership inference; fairness transparency; explainable/interpretable machine learning; deepfakes and disinformation.
Topics
- adversarial machine learning
- differential privacy
- membership inference
- fairness transparency
- explainable/interpretable machine learning
- deepfakes and disinformation
Topics explicitly listed in official catalogue description
Prerequisites & course information
Grading Scheme: Letter Grade Prerequisite: Knowledge of programming fundamentals, familiarity with machine learning and Python is a plus.
Sources
- Course catalogue ↗2025-2026