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Welcome to Mastering AI Agents Certification Program! 🚀
Whether you wrapped up Agentic AI Essentials program with a completed project or you're continuing your learning at your own pace — we’re excited to have you here as we kick off the next phase of your journey.
In Agentic AI Essentials, we laid the foundations: you explored how LLMs can be used to build smart assistants, designed multi-step workflows, and implemented powerful retrieval pipelines. Along the way, you picked up prompting techniques, memory management strategies, and system design patterns that turn static chatbots into dynamic assistants.
Now it’s time to level up.
Mastering AI Agents is where we shift from building assistants to building agents — systems that can reason, use tools, and operate more autonomously. We’ll introduce you to LangGraph, dive into multi-agent architectures, and show you how to scale your systems with tools, observability, and design patterns that are built for real-world complexity.
You’re not just using LLMs anymore — you’re engineering intelligence.
Let’s begin.
Before we dive into this unit’s lessons, we’re also introducing the Mastering AI Agents Project — your capstone for the next four units. This project will challenge you to apply everything you learn in Mastering AI Agents program to build and document a real, agentic system. You'll find a separate publication outlining the requirements, expectations, and submission details.
Here’s how the lessons for unit 1 are structured:
Lesson 1: From Workflows to Agents: When Predictable Paths Aren't Enough
Lesson 2: Building Agentic Systems at Scale: An Introduction to LangGraph
Lesson 3: Your First LangGraph Project: Building a Joke Bot
Lesson 4: Agentic AI With LangGraph: Building a Writer–Critic Loop
Lesson 5: Inside the Mind of an Agent: Observability with LangSmith
By the end of this unit, you'll have the skills to move beyond linear task flows and start building truly agentic systems. You’ll understand the building blocks of agent graphs, tool integration, and debugging workflows — all with real-world code.
Onward!
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