Building and Optimizing AI Agent Workflows

This long course equips you with practical knowledge and hands-on skills required to design, architect, and optimize autonomous AI agents that solve multi-step tasks reliably, efficiently, and responsibly. You will study reward-design and reinforcement-learning foundations to translate business objectives into robust reward signals, while learning to evaluate ethical, legal, and societal impacts of agent decision policies. The course covers competing reasoning-loop architectures (e.g., ReAct and Reflexion), modular agent component design with clear APIs, and search and planning strategies (A*,…