
As AI systems become more embedded in business operations, organizations face growing pressure to govern them responsibly, transparently, and in line with evolving regulations. This course explores how widely recognized AI regulations and industry frameworks can be translated into governance models that reflect real organizational contexts, priorities, and use cases.
Instructed by data management expert Irina Steenbeek, the course guides participants through analyzing AI regulations, risk classifications, and governance principles, while connecting them to AI strategy, lifecycle models, policies, and organizational roles. Emphasis is placed on drafting practical AI governance policies, defining responsibilities with RACI, assessing maturity, and understanding how deployment choices influence cost, risk, and oversight.
Course Highlights
Pricing and Credits
By the End of This Course, You’ll Be Able To:
Why Take This Course?
This course provides a structured approach to translating AI frameworks into organization-ready governance models. It covers practical structures for policies, roles, and risk management.
Is This Course Right for You or Your Team?
This course is ideal for:
No technical experience is required. This course is designed for business-focused professionals seeking to establish clear, responsible, and scalable AI governance aligned with organizational goals and regulatory expectations.
This Course Includes: