Generative AI for Data Privacy and Protection

As data breaches become more sophisticated, the tools used to protect information must evolve. Generative AI offers powerful new ways to safeguard privacy while maintaining the analytical value of your data. This course provides a comprehensive introduction to how these emerging technologies can be used to strengthen security and ensure compliance. You will gain the skills to transform raw data into secure assets using modern AI methodologies. By the end of this course, you will understand how to implement privacy-first workflows that utilize synthetic data and automated protection strategies. What you'll learn: - Understand the fundamental principles of data privacy and how Generative AI transforms traditional protection methods. - Apply techniques for generating high-quality synthetic data that preserves privacy without losing analytical value. - Learn to identify and mitigate privacy risks within Large Language Model prompts and responses. - Master the basics of PII (Personally Identifiable Information) detection and automated redaction using AI models. - Explore modern security patterns for Retrieval-Augmented Generation (RAG) and secure vector database management. - Practice implementing differential privacy concepts to ensure individual records remain protected during model interactions. The course begins with essential terminology and core privacy frameworks before moving into practical written exercises focused on synthetic data generation and secure AI integration. This course is designed for beginners interested in the intersection of AI and security, requiring no prior experience in data science or programming. Start your journey into the future of data protection by reading this foundational guide.