Designing Responsible AI: Security, Risk, and Compliance Fundamentals

As organizations rapidly adopt artificial intelligence, ensuring these systems are secure, ethical, and compliant is more critical than ever. Navigating the complex landscape of AI risks requires a structured, responsible approach from day one. This text-based course guides you through the essential principles of designing secure and governed AI systems, helping you transition from understanding core ethical concepts to applying practical risk management strategies that protect both users and organizational integrity. What you'll learn: Understand the foundational pillars of Responsible AI, including fairness, transparency, and accountability; Identify modern AI threat vectors such as prompt injection, data poisoning, and model inversion; Apply risk management lifecycles using established frameworks like the NIST AI Risk Management Framework; Evaluate security considerations for advanced patterns like Retrieval-Augmented Generation (RAG) and vector databases; Navigate key compliance standards and emerging global regulations, including the EU AI Act; Establish governance structures and policy guardrails to monitor AI systems post-deployment. The course begins with fundamental terminology and ethical principles before moving into practical security threats, risk assessment methodologies, and governance workflows. You will read detailed explanations, analyze real-world scenarios, and complete written exercises to solidify your knowledge. Designed for beginners, this course requires no prior background in cybersecurity or artificial intelligence development, making it ideal for aspiring risk analysts, compliance officers, and IT professionals looking to enter the field of AI governance. Start building your foundational knowledge in responsible AI security today.