In this module, we will walk you through the course agenda, helping you understand the topics covered and how the mission will unfold. You'll have a complete overview of what to expect in each section of the course.

In this module, we will cover the basics of Agentic AI, focusing on its foundational principles and the importance of agents in solving complex problems. You'll learn when to activate agents and explore their role in optimizing outcomes.

In this module, we will look at real-world applications of Agentic AI, comparing it with RAG, and exploring how agents make decisions using decision trees. You'll also participate in a field test to see the theory in action.

In this module, we will take a deep dive into the anatomy of an agent, examining its internal structure, functions, and advanced features. This will help you understand how agents work at a technical level.

In this module, we will guide you through the process of building your own AI agent. You'll begin with foundational steps and progress to advanced development techniques to create an agent suited for real-world tasks.

In this module, we will explore Bedrock Agents, their basic and advanced features, and their practical applications. You'll also work with agents through Jupyter Notebooks to deepen your understanding of their functionality.

In this module, we will focus on multi-agent systems, exploring how multiple agents work together to solve problems. You'll build your first multi-agent system and learn performance improvement techniques through practical examples and case studies.

In this module, we will recap the key takeaways from the course and provide guidance on your next steps. You'll be equipped with the tools and knowledge to continue applying Agentic AI in practical settings.

In this module, we will teach you how to estimate the cost of practicing the demos in AWS, focusing on cost-efficiency and best practices for managing cloud resources while keeping costs low.