This beginner-friendly course introduces the essential concepts and practical techniques for building AI agents. It begins with an overview of AI agents, explaining what they are, how they operate, and the frameworks used to develop them. Learners are guided through designing effective AI agents, understanding agentic RAG (Retrieval-Augmented Generation) systems, and applying the Agent Tool Use design pattern for practical workflows.

The course emphasizes hands-on deployment, teaching learners how to bring AI agents into production safely and efficiently. Techniques such as context engineering and using agentic protocols like MCP, A2A, and NLWeb are covered to optimize agent performance. Additionally, the course explains multi-agent systems, showing how to coordinate multiple AI agents to work together and solve complex tasks.

By the end of this course, participants will have the knowledge to design, implement, and deploy AI agents for various real-world applications. They will be able to choose the right frameworks, apply best practices in agent design, and leverage advanced techniques like RAG and context engineering to build effective, autonomous AI systems.