This course is for learners who want a foundation in AI governance and compliance, including professionals who oversee or support AI use in their organizations. It begins by defining artificial intelligence, tracing its evolution from early concepts to large language models, and weighing its potential benefits against its risks, including documented AI failures. It then defines AI governance and compliance and explains the core goals governance seeks to protect, such as safety, security, fairness, accountability, transparency, and privacy. Learners next study how to operationalize governance through its objectives and objects, using the AI lifecycle, governance targets, and four models of governance. The course closes by contrasting a governance mindset with a compliance mindset and showing why AI systems need continuous, feedback-driven oversight.