Complete Agentic AI Bootcamp With LangGraph and Langchain

Overview

Learn to build real-world AI agents, multi-agent workflows, and autonomous apps with LangGraph and LangChain What you'll learn:

Understand the core principles of Agentic AI and how to design intelligent, autonomous agents for real-world tasks.Master building AI agents using LangGraph, including creating workflows, managing agent state, memory, and event-driven behavior.Develop and deploy multi-agent collaborative systems that can communicate, reason, and solve complex problems together.mplement hands-on projects to create powerful agentic applications like autonomous research agents, task automation systems, and knowledge retrieval assistants. Are you excited about the future of AI where intelligent agents can think, act, and collaborate to solve complex tasks autonomously?

Welcome to the Complete Agentic AI Bootcamp with LangGraph and LangChain — your one-stop course to master the art of building agentic AI applications from scratch!This course is designed to teach you everything you need to know about Agentic AI, LangGraph, and LangChain — two of the most powerful frameworks for building intelligent AI agents and multi-agent systems.You will start by understanding the fundamentals of Agentic AI — how it differs from traditional AI models, the key components of agents (memory, tools, decision-making), and real-world use cases.We will then dive deep into LangGraph, a cutting-edge framework that helps you design complex agent workflows using graphs, events, and state transitions. You’ll also learn how to combine LangChain's power with LangGraph to build production-ready agent applications.Throughout the course, you will build real-world projects step-by-step, including:

Creating single intelligent agents with memory and tool-usage capabilities.Designing multi-agent collaboration systems with message passing and shared goals.Implementing autonomous research assistants, task automation bots, and retrieval-augmented generation (RAG) agents.You will not just learn theory — you will build and deploy multiple end-to-end agentic applications, gaining real-world experience in constructing powerful AI systems.By the end of this course, you will have the skills and confidence to create your own AI agents and deploy complex agentic applications for various domains like search, research, task planning, customer support, and beyond.What You Will Learn:

Core concepts behind Agentic AI and how intelligent agents operate.Hands-on mastery of LangGraph and LangChain for building agent systems.Building autonomous, event-driven AI workflows with memory, reasoning, and tools.Deploying and optimizing single-agent and multi-agent applications.Real-world project experience with RAG agents, auto-research agents, and more.Why Take This Course?Hands-on, Project-Based Learning:

Build actual AI agent applications, not just toy examples.Complete and Beginner-Friendly:

Designed to take you from beginner to advanced agent builder.Real-World Skills:

Learn techniques that companies are starting to use for next-generation AI products.Cutting-Edge Technologies:

Master the latest innovations in AI agent orchestration with LangGraph and LangChain.If you are a developer, data scientist, AI/ML engineer, or tech enthusiast looking to future-proof your skills and build cutting-edge AI applications, this is the course for you!Enroll now and start building the future with intelligent AI agents today!

Syllabus

• Introduction to Agentic AI
Understanding Agentic AI vs. Traditional AI
Key components of intelligent agents: memory, tools, decision-making
Real-world use cases of Agentic AI
• Fundamentals of LangGraph
Overview of the LangGraph framework
Designing complex workflows using graphs, events, and state transitions
Combining LangGraph with LangChain for enhanced capabilities
• Building Single Intelligent Agents
Creating agents with memory and tool-usage
Implementing event-driven behavior
Managing agent state and transitions
• Multi-Agent Systems and Collaboration
Designing systems with message passing and shared goals
Communication and reasoning between agents
Solving complex problems collaboratively
• Project: Autonomous Research Agents
Task automation and information retrieval
Integrating with external knowledge bases
Deploying and optimizing performance
• Project: Task Automation Bots
Building bots for repetitive task handling
Utilizing agent memory for contextual awareness
Workflow automation strategies
• Project: Retrieval-Augmented Generation (RAG) Agents
Incorporating retrieval techniques in agent designs
Developing content generation capabilities
Enhancing information accuracy and relevance
• Hands-on Mastery of LangGraph and LangChain
Practical exercises on building agent systems
Deploying single-agent and multi-agent applications
Real-world scenarios and case studies
• Course Conclusion
Review of core concepts and projects
Future trends in Agentic AI
Resources for continued learning and skill development

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Taught by

KRISHAI Technologies Private Limited and Krish Naik

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Subjects

Computer Science