LangGraph- Develop LLM powered AI agents with LangGraph
Build LangGraph agents in Python: Reflexion, Agentic RAG, memory & human-in-the-loop, deployment for LangChain devs
Lo que serás capaz de hacer
Welcome to first LangGraph Udemy course ! This comprehensive course is designed to teach you how to QUICKLY harness the power the LangGraph library for LLM agentic applications. This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM Agents solutions for a diverse range of topics. Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python & LangChain. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts . Course map Concepts (≈ 42m): what LangGraph is, graphs, flow engineering, core components Agent patterns (≈ 4h, shared with the LangChain course): Reflection, Reflexion, Agentic RAG (Corrective/Self/Adaptive), ReAct with ToolNode LangGraph-only (≈ 2h50m): persistence & interrupts, async execution, Studio & LangSmith Deployment, GPT-Researcher, CopilotKit The topics covered in this course include: LangChain LCEL LangGraph Agents Multi Agents Reflection Agents Reflexion Agents LangSmith CrewAI VS LangGraph Advanced RAG Corrective RAG Self RAg Adaptive RAG GPT Researcher LangGraph Ecosystem: LangGraph Studio / LangGraph IDE LangGraph Cloud API LangGraph Cloud Managed Service Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LangGraph to create powerful, efficient, and versatile LLM applications for a wide array of usages. This is not just a course, it's also a community. Along with lifetime access to the course, you'll get: Dedicated troubleshooting support with me Github links with additional AI resources, FAQ, troubleshooting guides No extra cost for continuous updates and improvements to the course Who this course is for AI Engineers, Software, backend and full-stack engineers who know LangChain and want stateful agents with LangGraph LangChain-course graduates who want the LangGraph-only sections (6–10) — see the overlap note This course is not for you if: You're new to Python or LangChain You want a source-level tour of LangGraph's internals and abstract classes You want a concept-first, lecture-heavy course
- Model agent workflows as graphs: state, nodes, conditional edges and cycles
- Build Reflection and Reflexion agents that critique and revise their own output
- Build Corrective, Self and Adaptive RAG agents with LangGraph and Tavily web search
- Rebuild a ReAct agent in LangGraph with ToolNode and function calling
- Add memory and human-in-the-loop with MemorySaver, SqliteSaver and interrupts
- Run nodes in parallel with async fan-out/fan-in and conditional branching
Temario
UNIDAD 1 - Introduction · 9 leccionesUNIDAD 1 - Introduction
UNIDAD 1 - Introduction
- Intro
- Prerequisites (Please Watch this before enrolling)
- Course Community
- What is LangGraph
- Why LangGraph and AI Agents Applications
- But wait.. What are Graphs?
- Flow Engineering
- LangGraph Core Components
- Course Resources
UNIDAD 2 - Reflection Agent · 7 leccionesUNIDAD 2 - Reflection Agent
UNIDAD 2 - Reflection Agent
- What are we building?
- Project Setup
- Creating the Reflector Chain and the Tweet Revisor Chain
- Defining our LangGraph Graph
- Defining our LangGraph Graph
- LangSmith Tracing
- Personal Message
UNIDAD 3 - Reflexion Agent · 11 leccionesUNIDAD 3 - Reflexion Agent
UNIDAD 3 - Reflexion Agent
- What are we building?
- Section Resources
- Project Setup
- Actor Agent
- Revisor Agent
- ToolNode - Executing Tools
- [Optional] Tool Executor Agent (Part A)- Life Before ToolNode
- [Optional] Tool Executor Agent (Part B)- Life Before ToolNode
- [Optional] Tool Executor Agent (Part C)- Life Before ToolNode
- [NEW] Building Our LangGraph Graph
- [New] Tracing Our Graph
UNIDAD 4 - Agentic RAG Flows · 14 leccionesUNIDAD 4 - Agentic RAG Flows
UNIDAD 4 - Agentic RAG Flows
- What are Building In this Section- Agentic RAG Architecture
- Improving RAG Quality with the Corrective RAG Flow
- Boilerplate Setup for an Agentic RAG Agent with LangGraph
- Code Structure
- LangChain Vector Store Ingestion Pipeline (UnstructuredLoader, ChromaDB)
- Managing Information Flow in LangGraph: The GraphState
- Fetching Context for LLMs: The LangGraph Retrieve Node
- Building a Relevance Filter for RAG using LangChain's Structured Output
- Implementing a Web Search Node in LangGraph using Tavily API
- Creating the LLM Generation Chain and Node for LangGraph
- Building and Running the Complete LangGraph Agent
- Self RAG Intro
- Self RAG- Implementation
- Adaptive RAG- Implementation
UNIDAD 5 - Implementing ReAct AgentExecutor with LangGraph · 6 leccionesUNIDAD 5 - Implementing ReAct AgentExecutor with LangGraph
UNIDAD 5 - Implementing ReAct AgentExecutor with LangGraph
- What are we building? ReAct AgentExecutor in LangGraph
- Get Started: Setting Up Your ReAct Agent Project Environment
- Coding the Agent's Brain: Implementing the ReAct Runnable
- Building Blocks: Defining Your Agent's Nodes in LangGraph
- Bringing Your ReAct Agent to Life: Connecting Nodes into a Graph
- Running Our LangGraph React Agent with Function Calling
UNIDAD 6 - Persistence · 4 leccionesUNIDAD 6 - Persistence
UNIDAD 6 - Persistence
- Persistence in LangGraph
- MemorySaver + Interrupts = Human In The Loop
- MemorySaver
- SqliteSaver
UNIDAD 7 - Run graph asynchronously · 4 leccionesUNIDAD 7 - Run graph asynchronously
UNIDAD 7 - Run graph asynchronously
- Implementing Async Execution
- Parallel node fan-out and fan-in with extra steps
- Conditional Branching With Async Execution
- Async Nodes Benefits VS Challenges
UNIDAD 8 - LangGraph Ecosystem- LangGraph Studio, LangGraph Cloud API, LangGraph Cloud · 5 leccionesUNIDAD 8 - LangGraph Ecosystem- LangGraph Studio, LangGraph Cloud API, LangGraph Cloud
UNIDAD 8 - LangGraph Ecosystem- LangGraph Studio, LangGraph Cloud API, LangGraph Cloud
- Intro
- LangGraph Studio (AKA LangGraph IDE)
- LangGraph Cloud API - Environment Setup (Local)
- LangSmith Deployment API Deep Dive - Assistants, Threads, Runs (Local)
- Deploying to LangSmith Deployment
UNIDAD 9 - Production featuring GPT-Researcher · 7 leccionesUNIDAD 9 - Production featuring GPT-Researcher
UNIDAD 9 - Production featuring GPT-Researcher
- Agents In Production
- LangGraph VS CrewAI main difference
- GPT Researcher
- GPT Researcher - Setup
- GPT Researcher - Architecture
- Multi Agent Architecture
- Deep Research with Assaf Elovic
UNIDAD 10 - Production Featuring CopilotKit · 4 leccionesUNIDAD 10 - Production Featuring CopilotKit
UNIDAD 10 - Production Featuring CopilotKit
- Generative UI
- HIL
- Agent Human Interaction - Part 1
- Agent Human Interaction - Part 2
UNIDAD 11 - Troubleshooting Section · 1 leccionesUNIDAD 11 - Troubleshooting Section
UNIDAD 11 - Troubleshooting Section
- Have a technical issue? WATCH THIS FIRST. I Promise this will help!
UNIDAD 12 - Bonus · 1 leccionesUNIDAD 12 - Bonus
UNIDAD 12 - Bonus
- Bonus
Tu certificado lo emite la SEP, no solo una plataforma
Al demostrar la competencia recibes un certificado emitido por la Secretaría de Educación Pública a través del Gobierno del Estado de México: un documento oficial que puedes presentar con confianza ante cualquier empleador o institución.
Tu certificado con INEC
- Lo emite la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México
- Documento oficial con folio verificable en línea
- Lo otorga la Universidad Tecnológica Fidel Velázquez
Otras plataformas en línea
- Constancia privada emitida por la misma plataforma
- Solo acredita horas cursadas o asistencia
- Sin respaldo de una autoridad educativa
Tu itinerario, de la inscripción al certificado
- 1
Inscripción con pago único
Pagas $2,800 MXN una sola vez y entras de inmediato al curso.
- 2
Estudias a tu ritmo
12 unidades con videos, lecturas y actividades, disponibles 24/7 durante 12 meses.
- 3
Cuestionarios por unidad
Cuestionarios para comprobar lo aprendido.
- 4
Certificado
Emitido por la SEP a través del Gobierno del Estado de México, con folio verificable.
Un certificado oficial de la SEP
Muestra · verificable por folio y QR
- Emitido por la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México. No es una constancia privada: es un documento oficial, y ese respaldo marca la diferencia frente a otras plataformas en línea.
- Contenido impartido por Eden Marco.
- Folio y QR verificables para compartirlo con quien te contrate.
Empieza hoy, a tu ritmo
Un solo pago y acceso inmediato al curso completo durante 12 meses.
- 12 unidades · 73 lecciones · 60 h
- 12 meses de acceso
- Certificado emitido por la SEP (Gob. del Estado de México) con folio verificable
Sobre tu inscripción
¿Cómo es el pago?
Un solo pago de $2,800 MXN. No hay mensualidades ni cargos recurrentes.
¿Cuánto tiempo tengo acceso?
12 meses desde tu inscripción, 24/7, para avanzar a tu ritmo.
¿Quién imparte el contenido?
El curso es impartido por Eden Marco; INEC gestiona tu inscripción, evaluación y certificado.
¿Qué pasa cuando vence mi acceso?
Puedes renovar tu cuenta tú mismo desde la plataforma, sin trámites ni esperas.
