This course is designed for anyone who wants to gain a deeper understanding about the importance of trust and responsibility in agentic AI and AI agents. The content is especially geared to those who are making business decisions based on AI agents and agentic AI and those who are designing and training such systems.

1. Distinguish between traditional AI agents and agentic AI systems in terms of scope, autonomy, and decision-making. 2. Apply six core ethical principles to real-world predictive modeling workflows and agentic system design. 3. Evaluate ethical considerations across five industry domains using structured scenario analysis. 4. Utilize practical tools—including documentation templates, ethics checklists, and governance prompts—to design trustworthy systems. 5. Understand emerging regulatory frameworks including the EU AI Act, U.S. federal and state regulations, and global AI governance resources. Who Should Attend: Data consumers, IT professionals, managers, analysts, data scientists, and anyone else who uses, designs, consumes information from, or makes decisions based on data and AI Prerequisites: 1. Responsible Innovation and Trustworthy AI