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A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Artificial Intelligence is transforming industries, but without proper governance it can introduce serious risks, ethical challenges, and regulatory consequences. In this course, you will build a strong foundation in AI governance and learn how organizations design responsible AI frameworks that balance innovation with accountability. You will explore the principles of responsible AI, risk management strategies, and governance structures that help organizations deploy AI systems safely and ethically. The course begins by introducing the AIGP certification, its exam structure, and the core objectives required to succeed. You will then explore the foundations of AI governance, including AI types, governance principles, organizational roles, and lifecycle-based governance strategies. Through real-world examples, you will understand how organizations establish governance teams, develop policies, and embed ethical oversight into AI systems. As the course progresses, you will examine global AI regulations, standards, and frameworks such as the EU AI Act, OECD AI Principles, and NIST AI Risk Management Framework. You will also explore key legal responsibilities, data protection requirements, intellectual property challenges, and risk classification models used to manage AI systems responsibly. This course is ideal for privacy professionals, compliance officers, AI practitioners, technology leaders, and policy specialists seeking to understand AI governance and prepare for the AIGP certification. A basic understanding of AI concepts, data governance, or technology management is helpful but not required. The course is designed at an intermediate level for professionals looking to develop governance expertise in AI systems. By the end of the course, you will be able to design AI governance frameworks, interpret global AI regulations, implement AI risk management processes, and evaluate AI systems for responsible and compliant deployment.