Greater Insights
Learning simplified!
Master Agentic AI with LangChain and LangGraph in Chennai — move into LLM Agent Developer roles paying ₹14–28 LPA, rising to ₹48L at senior level.
Designs and deploys autonomous AI agents using LLMs, chains, and external tools to solve complex tasks.
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Builds intelligent agents with LangChain and LangGraph, integrating reasoning chains and tool integrations.
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Creates production-ready generative AI applications using LLM-powered workflows and retrieval systems.
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* Salary figures sourced from AmbitionBox (2026-Q2). Indicative — actual pay varies by city, company and experience.
Open-house batches for individuals — enroll directly. Training a team? Request an enterprise quote →
| Dates | Schedule | Mode | Duration | Price | |
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28 Sep – 02 Oct 2026
Monday
all session dates
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9:30 AM–5:30 PM IST | 🎓 Virtual Instructor-led | 5 days | ₹21,000 ₹35,000 |
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Mon 28 SepTue 29 SepWed 30 SepThu 1 OctFri 2 Oct
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03 Oct – 01 Nov 2026
Saturday
all session dates
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10:00 AM–2:00 PM IST | 🎓 Virtual Instructor-led | 5 weekends | ₹21,000 ₹35,000 |
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Sat 3 OctSun 4 OctSat 10 OctSun 11 OctSat 17 OctSun 18 OctSat 24 OctSun 25 OctSat 31 OctSun 1 Nov
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| Enterprise Custom Date |
Custom Schedule Your timing & location |
⚡ Any Mode | Flexible | Custom pricing | |
Can't find a suitable batch? Contact us
This intermediate course teaches you to design and build intelligent LLM-powered agents using LangChain and LangGraph. You'll learn to construct multi-step reasoning chains, model stateful workflows, and integrate external tools and APIs into agentic systems. The course covers core patterns like ReAct reasoning, retrieval-augmented generation, and multi-agent orchestration, equipping you with hands-on skills in prompt engineering, memory implementation, error handling, and human-in-the-loop design.
Ideal for AI engineers, LLM application developers, and ML engineers seeking to move beyond single-turn interactions, this course guides you through building production-ready agents. Using LangChain, LangGraph, LangSmith, OpenAI API, FAISS, Chroma, Pinecone, and Python, you'll construct agents that reason, retrieve knowledge, collaborate, and expose their capabilities as REST APIs. You'll gain practical experience debugging agent behavior, defining custom tools with validation, and deploying agentic applications in real-world scenarios.
The job roles this programme is built for.
8 modules · hands-on labs · 1 capstone project · 38 hours
Every batch includes guided labs, case studies and a capstone — applied to real-world problems.
Everything your programme needs, in one connected place.
No install. No config. Just build.
Not email, Zoom links and scattered PDFs. From the moment you enroll, your whole programme lives in one place.
From enrolment to certificate, every step is laid out in order — you always know where you are and exactly what happens next. Nothing lost between tools.
Pre-configured cloud labs. Spin one up in seconds, build on real infrastructure, break things and learn — nothing to install.
Write and run code right in the browser, get AI feedback as you go, and practice against problems that mirror the job — no local setup, ever.
A pre-assessment sets your baseline; a post-assessment proves your uplift. Real, measurable growth — for you, and for the employer looking at your record.
A capstone graded by AI and validated by your trainer — detailed feedback in hours, not weeks, on work that looks like what teams actually ship.
Today's session, pending tasks, resources and progress — organised in one place so you focus on learning, not on chasing links and files.
One verifiable link — the project you built, your before → after scores, the skills you proved. Shareable with any employer.
Earn your Greater Insights Agentic AI with LangChain and LangGraph certificate — ready to share on LinkedIn.
Verified Google reviews — Greater Insights company-wide
This intermediate programme teaches you to design, build, and deploy production-grade agentic AI systems using LangChain and LangGraph. Delivered live by an expert instructor, every session combines conceptual grounding with hands-on Python labs in Jupyter Notebooks. You progress from foundational agentic concepts through multi-agent orchestration, retrieval-augmented generation, and human-in-the-loop workflows, culminating in a capstone project where you package and containerise a fully functional agentic application using FastAPI and Docker.
Agentic AI refers to systems in which a large language model does not simply respond to a single prompt but instead reasons, plans, and acts across multiple steps — calling external tools, managing memory, and adapting its behaviour based on intermediate results. LangChain provides the foundational primitives: chains, runnables, prompt templates, output parsers, and a rich tool ecosystem including the Tavily Search API and Wikipedia API. LangGraph extends this by modelling agent behaviour as explicit stateful graphs of nodes and edges, enabling loops, conditional branching, parallel execution, and interrupts. Together they form a production-ready stack for building agents that integrate with vector stores such as FAISS, Chroma, and Pinecone, and communicate with frontier models through the OpenAI API and Anthropic Claude API.
Enterprises are moving rapidly from experimental LLM demos to autonomous agents embedded in real workflows — research assistants, coding agents, data analysis pipelines, and approval-gated decision systems. The engineers who can construct these systems with LangChain and LangGraph, instrument them with LangSmith observability, and ship them inside Docker containers behind FastAPI endpoints are commanding serious attention from hiring teams. Proficiency in multi-agent collaboration patterns, adaptive RAG, human-in-the-loop interrupts, and robust error handling and fallback logic distinguishes practitioners who build reliable agentic products from those who only prototype. This course gives you exactly that production-oriented skill set.
By the end you will have built — not just studied — the core systems of the field:
Completing this course positions you for roles including AI Engineer, LLM Application Developer, Generative AI Developer, Conversational AI Developer, and AI Solutions Architect, as well as backend engineering positions where AI-powered services are the core product. Demand for engineers who can move beyond prompt experimentation and build observable, debuggable, production-deployed agent systems is growing sharply across technology companies, AI-native startups, and enterprise digital transformation teams. Proficiency in the LangChain and LangGraph stack, combined with practical experience in LangSmith tracing, multi-agent orchestration, RAG integration, and Docker-based deployment, makes a candidate genuinely distinctive. Research Engineer roles at applied AI labs also value the evaluation, observability, and systematic debugging skills developed throughout this programme.
Designing an autonomous agent that can route customer queries, call external APIs, and recover gracefully from tool failures is the kind of challenge that defines day-to-day work for LangChain and LangGraph professionals in Chennai. Teams at TIDEL Park in Taramani and Global Infocity Park in Perungudi are building exactly these systems — multi-step pipelines where an orchestration graph manages state, handles conditional branching, and decides when to invoke a retrieval tool versus a generative response. Whether you are working within the enterprise delivery operations of firms like TCS, Cognizant, or Wipro, or inside the product engineering culture of Freshworks or Zoho, the ability to design reliable agentic workflows has become a core expectation rather than a specialist niche.
Employers in Chennai that recruit for Agentic AI with LangChain and LangGraph skills include Zoho and Freshworks, both of which embed AI capabilities directly into their product lines, alongside Cognizant, Wipro, and TCS, which staff large-scale AI delivery practices from the city. HCL, Saint-Gobain, and Ashok Leyland also employ professionals who apply agentic frameworks to supply chain intelligence, industrial automation, and connected enterprise workflows.
Demand for these roles grows year on year as organisations move from isolated model experiments toward production-grade autonomous systems that require the structured graph-based approach LangGraph provides. You can build this skill set without disrupting your current commitments, as live online instructor-led batches run in IST and are joinable from anywhere in Chennai.
