Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you'll gain a solid foundation in Agentic AI, starting with its basic principles and advancing to real-world applications. You will learn to build and deploy AI agents, understand the inner workings of these agents, and dive into multi-agent systems. The course is designed to equip you with the practical skills needed to create and manage intelligent agents that solve complex problems. As you progress, you will explore various agent architectures and gain hands-on experience with real-world AI tools, such as Bedrock Agents. This course provides a perfect blend of theory and practice, with guided exercises that help reinforce your learning. Through live demos and building your agents, you’ll see how these systems perform in real-world scenarios. This course is ideal for anyone interested in AI, machine learning, or building smart applications. No prior experience with Agentic AI is required, although basic programming knowledge will be beneficial. Whether you're a beginner or someone with a technical background, you’ll gain the skills necessary to develop and deploy AI agents in various industries. By the end of the course, you will be able to: create and deploy Agentic AI, analyze multi-agent systems, develop decision trees, and optimize agent performance in real-world scenarios.

Syllabus

Pre-Mission Briefing

In this module, we will introduce the structure of the course, explain its objectives, and set expectations for your learning journey. You'll get familiar with the mission and what you'll be learning in upcoming sections.

Operation Plan (Agenda)

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.

Bootcamp Basics

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.

Real-World Ops

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.

Classified: Agent Internals

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.

Operation Agent Forge: Engineering Your AI Agents

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.

Command Center: Working with Bedrock Agents

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.

Squad Tactics - Multi-agent Mission

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.

Mission Debrief - Key Takeaways & Next Steps

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.

How much it will cost in AWS billing for practicing the demos?

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.