This course introduces the foundations and practical implementation of AI governance, helping organizations design and manage responsible AI systems.
You’ll begin by understanding core governance concepts, stakeholder roles, and how governance differs from ethics and compliance. The course then explores global frameworks such as the EU AI Act and NIST AI RMF, enabling you to align AI systems with regulatory expectations. Next, you’ll learn how to operationalize governance through policy design, maturity models, and lifecycle risk management using tools like risk registers and impact assessments. The course also covers monitoring, auditing, and incident response to ensure continuous oversight of AI systems. By the end of this course, you will be able to: - Explain AI governance fundamentals and stakeholder roles - Apply global frameworks to real-world AI systems - Design policies and manage lifecycle risks - Monitor, audit, and respond to AI risks Designed for professionals, analysts, and anyone working with AI systems, this course provides a structured approach to implementing AI governance in practice. To be successful, learners should have a basic understanding of AI concepts and business processes. Start your journey into responsible AI and learn how to build governance systems that ensure accountability and trust.
