Implementing AI Security Controls and Defenses

As artificial intelligence becomes central to modern software, securing these systems against unique vulnerabilities like prompt injection and data leakage is more critical than ever. This text-based course guides you through the essential concepts and practical strategies needed to protect AI deployments. You will learn how to transition from basic AI setups to highly secure environments using industry-standard defense mechanisms and zero-trust principles. What you'll learn: - Understand foundational AI vulnerabilities, including prompt injection and data poisoning. - Configure robust content filters and metaprompts to govern model inputs and outputs. - Apply data security and grounding techniques to prevent unauthorized data exposure. - Implement continuous monitoring and observability to detect anomalous AI behavior. - Integrate zero-trust security concepts into your overall AI architecture. The course begins with core terminology and the modern threat landscape, before moving into step-by-step written explanations of defense configurations, grounding, and monitoring strategies. It is designed for software developers, IT professionals, and security beginners looking to safeguard AI applications, with no advanced machine learning experience required. Start reading today to build safer, more resilient AI systems.