igmGuru's LangGraph Course helps developers move from LangChain basics to building stateful, production-grade multi-agent systems through live instructor-led sessions, hands-on labs, real deployment projects, and dedicated career support for engineers.
✅ Level - Beginner to Intermediate ✅ 30-Hour Live, Instructor-Led Training ✅ 100% Hands-On Agentic AI & Multi-Agent Projects ✅ Curriculum Aligned with Official LangGraph & LangChain Documentation ✅ Real LangSmith Debugging, Tracing & Deployment Labs ✅ Trainers with Production-Grade GenAI Experience ✅ Watch First Class For Free
LangGraph is LangChain's open-source, graph-based framework for building stateful AI agents that branch, loop, and recover from errors instead of following one fixed path. This LangChain course walks you through nodes, edges, state schemas, checkpointing, and human-in-the-loop controls, then puts them to work in real multi-agent projects. By the end of the program, you'll be able to design, debug with LangSmith, and deploy production-ready agentic applications on your own, backed by igmGuru's mentor support and hands-on project feedback.
You don't need prior agent-building experience, but the following will help you keep pace with the live sessions:
AI agents in 2026 don't run on a single prompt-and-response loop anymore. They branch, retry, wait for human approval, and pick up exactly where they left off after a crash and LangGraph is the framework most teams reach for to build that kind of behavior. Because LangChain 1.0 now runs on LangGraph under the hood, learning LangGraph is no longer a niche add-on skill; it has effectively become the default orchestration layer across the LangChain ecosystem.
Organizations including Uber, JPMorgan, BlackRock, Cisco, Klarna, CyberArk, and Replit already run LangGraph-based agents in production, and the open-source library has crossed roughly 31,000 GitHub stars, a sign of how quickly adoption is moving. With LangGraph 1.0 adding durable execution, time-travel debugging, and enterprise-grade checkpointing, the framework has matured well past the experimentation stage. For developers, that shift shows up as a fast-growing list of job titles- Agentic AI Engineer, LLM Application Developer, AI Workflow Architect- that now specifically call out LangGraph experience, making it one of the more future-proof additions to a GenAI resume today.
By the end of this course, you will be able to:
Across the training, you will work through these core building blocks of LangGraph:
This course is built for:
On completion, you'll walk away with these practical, job-ready skills:
LangGraph skills open doors to roles such as:
| Experience Level | India Salary (Annual CTC) | USA Salary (Annual) |
|---|---|---|
| Beginner (0-2 Years) | ₹3.5 - ₹8 LPA | $98,945 - $112,424 |
| Intermediate (2-5 Years) | ₹8 - ₹16 LPA | $123,128 - $145,000 |
| Experienced (5+ Years) | ₹20 - ₹45 LPA | $154,000 - $270,015 |
Here's what makes igmGuru's LangGraph training different:
On completing igmGuru's LangGraph course including the required modules, assignments, and the multi-agent capstone project, you will receive igmGuru's own industry-recognized Course Completion Certificate with lifetime validity. Alongside the certificate, we encourage you to publish their capstone project on GitHub with LangSmith traces attached, since a working, traceable agent project currently carries more weight with hiring managers than any single exam badge in this space.
Yes. LangGraph is released under the MIT license, so you can use, modify, and ship it commercially at no cost. Paid layers like LangSmith (observability) and LangSmith Deployment are optional add-ons for teams that want managed hosting and monitoring.
LangChain gives you building blocks- prompts, chains, tool wrappers. LangGraph adds a graph layer on top so those pieces can branch, loop, and persist state, which is why LangChain 1.0 now runs on LangGraph internally. CrewAI, by comparison, is role-based and more opinionated about how agents collaborate, while LangGraph gives you lower-level control over the exact flow.
Yes. Every live session is recorded, and you get lifetime access to those recordings along with the notes, code, and slides used in class.
Yes, both are available. Individual learners can check EMI options at checkout, and teams can request a customized corporate batch with flexible scheduling through our corporate training desk.
Yes. The curriculum is reviewed against LangGraph's official documentation and updated whenever a major release, like LangGraph 1.0 or LangChain 1.0, changes core APIs or best practices.
A laptop with at least 8GB RAM, Python 3.10 or higher, and an IDE such as VS Code. Access details for LangSmith and any LLM API keys used in class are shared before Module 1 so you're ready to code from day one.
Yes. Weekday evening and weekend batches are both available, sessions are recorded for catch-up, and mentors are reachable outside class hours for doubt-clearing.
