Generative AI Security: Protecting Data & Models Made Easy
Generative AI Security: Protecting Data & Models Made Easy, Learn GenAI Security, AI Threat Modeling, Data Protection, and Model Safeguarding with Real-World Examples & Techniques.
Course Description
As Generative AI (GenAI) continues to revolutionize industries, it also introduces a new frontier of cybersecurity threats. From model theft and prompt injection to data leaks and algorithmic manipulation—there are critical risks every AI professional, developer, and business leader must understand.
This course is designed to help you understand the intersection of GenAI and cybersecurity in a practical, beginner-friendly way. You’ll explore how GenAI systems can be attacked, what threat modeling looks like for AI workflows, and how to safeguard sensitive data and intellectual property. Whether you’re working on AI projects, auditing digital systems, or simply exploring the future of technology, this course will equip you with essential knowledge to make GenAI systems more secure and responsible.
What you’ll learn:
- Core concepts of GenAI and why cybersecurity matters more than ever
- Common threats, risks, and real-world GenAI attack examples
- AI threat modeling fundamentals
- Data security issues and how to protect data in GenAI workflows
- How to secure AI models from theft, misuse, and replication
- Techniques like DRM, watermarking, and obfuscation for protection
No prior AI or cybersecurity experience is required. If you’re a student, tech professional, founder, or just GenAI-curious—this course is for you.
Join now and start securing the future of AI—one model at a time.
