LangGraph for beginners : Agentic Workflows in simple steps
What you'll learn
- What LangGraph is and how it fits into the GenAI ecosystem
- Build your first LangGraph workflow using a state machine
- Validate and structure your state using Pydantic models
- Use async and streaming to build responsive applications
- Implement conditional routing based on LLM output
- Understand reducers and how they manage state transitions
- Master tool calling with LangGraph’s built-in ToolNode
- Learn about checkpointers, and apply both short-term (in-memory) and long-term (SQLite, Redis) memory storage
- Build Agentic RAG workflows using tools and retrievers
- Implement Human-in-the-Loop workflows using Interrupt and resume
- Modularize complex graphs using subgraphs
- Apply everything in a real-time Hospital Insurance Claim Management use case
- Add tracing and observability using LangSmith
- Explore essential agentic design patterns to scale your applications
- All in simple steps
Requirements
- Knowledge of Python
- Experience with LangChain
Description
Are you ready to go beyond simple LLM apps and build powerful, stateful, and agentic workflows using LangGraph?
In this beginner-friendly course, you’ll master LangGraph, an open-source library built on top of LangChain, designed for orchestrating multi-agent applications using a graph-based architecture. Whether you’re building intelligent agents, dynamic RAG pipelines, or real-world enterprise solutions, this course gives you the solid foundation you need.
What You’ll Learn
• What LangGraph is and how it fits into the GenAI ecosystem
• Build your first LangGraph workflow using a state machine
• Validate and structure your state using Pydantic models
• Use async and streaming to build responsive applications
• Implement conditional routing based on LLM output
• Understand reducers and how they manage state transitions
• Master tool calling with LangGraph’s built-in ToolNode
• Learn about checkpointers, and apply both short-term (in-memory) and long-term (SQLite, Redis) memory storage
• Build Agentic RAG workflows using tools and retrievers
• Implement Human-in-the-Loop workflows using Interrupt and resume
• Modularize complex graphs using subgraphs
• Apply everything in a real-time Hospital Insurance Claim Management use case
• Add tracing and observability using LangSmith
• Explore essential agentic design patterns to scale your applications
Who This Course Is For
• AI developers looking to build production-grade agentic apps
• LangChain users who want to level up to graph-based orchestration
• Backend engineers interested in tool use, memory, and state control
• Anyone working on LLM workflows in real-world use cases
Prerequisites
• Basic Python knowledge
• Some familiarity with LangChain
By the end of this course, you’ll be able to:
• Confidently build, scale, and debug LangGraph workflows
• Integrate LLMs, tools, memory, and human feedback into your apps
• Apply LangGraph in real-world business use cases like claim processing, customer support, and document analysis
Ready to master LangGraph and take your LLM applications to the next level?
Enroll now and start building intelligent, interactive agentic systems with ease!
Who this course is for:
- Students who have taken my LangChain course and want to master LangGraph
Instructor
Bharath Thippireddy is an Entrepreneur, Software Architect,Actor and Public Speaker who has trained 8,00,000+ students across the planet. He is an Oracle Certified Developer, Web Component Developer, Business Component Developer, and Web Services Developer.
He loves learning new things both in technology and personal development and shares them on YouTube and his website. He has mentored students in classroom trainings as well as in the corporate world in both India and the USA. He has spoken on technical topics at several agile conferences. While in India, he also voluntarily teaches interview and soft skills at Vivekananda Kendra.
His trainings will help you master Full Stack Development using Java, Python, JavaScript, DevOps, AWS, Docker, Kubernetes, as well as Generative AI tools like OpenAI, LangChain, Azure OpenAI, and Copilot for developers.
From 40+ courses, which currently have 800K+ learners, you can pick a track and master:
• Generative AI tools such as OpenAI, LangChain, Azure OpenAI, and GitHub Copilot
• Spring Boot Project Development using Angular and React
• Angular and React project creation with Java or Node backend
• Complete Python Stack from core Python to Django REST Framework
• Docker, Kubernetes, Maven, Jenkins, GIT, AWS EC2, Elastic Beanstalk, ELB, Auto Scaling, and more in easy steps
• Java (Java Design Patterns, Java Web Services, Java Messaging Service)
• Spring modules (Spring Security, Spring Boot, Spring Data using Hibernate, Spring Data REST)
• Serverless programming using AWS Lambda