Intro to Differential Privacy & Synthetic Data

This lesson explores two important privacy-enhancing technologies used in AI and data analytics. Learners discover how differential privacy uses mathematical techniques to protect individual contributions within datasets and how synthetic data generates artificial records that preserve useful patterns while reducing privacy exposure. The lesson examines privacy-utility tradeoffs, privacy budgets, data sharing challenges, and the growing role of privacy-preserving technologies in responsible AI development.