Bootcamp Complet d'IA Agentique avec LangGraph et Langchain

Aperçu

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!

Programme

• Introduction à l'IA Agentique
Compréhension de l'IA Agentique vs. l'IA Traditionnelle
Composants clés des agents intelligents : mémoire, outils, prise de décision
Cas d'utilisation réels de l'IA Agentique
• Fondamentaux de LangGraph
Aperçu du cadre LangGraph
Conception de flux de travail complexes en utilisant des graphes, des événements et des transitions d'état
Combinaison de LangGraph avec LangChain pour des capacités améliorées
• Création d'Agents Intelligents Individuels
Création d'agents avec mémoire et utilisation d'outils
Mise en œuvre de comportements déclenchés par des événements
Gestion de l'état et des transitions de l'agent
• Systèmes Multi-Agents et Collaboration
Conception de systèmes avec passage de messages et objectifs partagés
Communication et raisonnement entre agents
Résolution collaborative de problèmes complexes
• Projet : Agents de Recherche Autonomes
Automatisation des tâches et recherche d'informations
Intégration avec des bases de connaissances externes
Déploiement et optimisation des performances
• Projet : Bots d'Automatisation des Tâches
Création de bots pour la gestion de tâches répétitives
Utilisation de la mémoire de l'agent pour une conscience contextuelle
Stratégies d'automatisation des flux de travail
• Projet : Agents de Génération de Contenu enrichie par la Récupération (RAG)
Incorporation de techniques de récupération dans la conception d'agents
Développement de capacités de génération de contenu
Amélioration de l'exactitude et de la pertinence de l'information
• Maîtrise Pratique de LangGraph et LangChain
Exercices pratiques sur la création de systèmes d'agents
Déploiement d'applications mono-agent et multi-agent
Scénarios réels et études de cas
• Conclusion du Cours
Révision des concepts et des projets principaux
Tendances futures de l'IA Agentique
Ressources pour l'apprentissage continu et le développement des compétences

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Enseigné par

KRISHAI Technologies Private Limited and Krish Naik

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Matières

Computer Science