Live Online · Developer Track · Batch Size 10
The newest specialisation in AI engineering, taught honestly. Learn to build AI agents with LangGraph and CrewAI — tool calling, multi-agent systems, agentic RAG, evaluation and guardrails — and deploy them for real. ₹35,000 with 100% placement support. Next batch: July 12, 2026.

Autonomous agents compound errors — we teach the constraints (evaluation, guardrails, human-in-the-loop) that make agents production-safe, not conference-demo magic.
Agentic AI is the newest, least-crowded specialisation in AI hiring. Candidates with deployed LangGraph/CrewAI projects are rare — your portfolio stands out.
This is a Python engineering course — not a no-code tour. You write, test, and deploy every agent you build.
New to agents entirely? Read the free explainer AI Agents Explained first. Looking for no-code business automation with n8n instead of Python agent engineering? That is the AI Automation Course — a different track for a different goal.
MODULE 1
Model APIs (GPT-5, Claude, Gemini), structured output, function/tool calling — the primitives every agent is built from.
MODULE 2
Build a research agent that plans, calls tools (search, code, APIs), and handles failures — the core agent loop.
MODULE 3
Graph-based agent design: state machines, conditional edges, persistence, streaming — how serious teams structure agents.
MODULE 4
Role-based agent teams, task delegation, agent-to-agent communication — and when multi-agent is overkill.
MODULE 5
Agents that decide what to retrieve and when — combining retrieval, reasoning and tool use over private data.
MODULE 6
Why demos lie: compounding error rates, eval harnesses, output validation, and safety guardrails for production.
MODULE 7
Approval checkpoints, escalation, and audit trails — how real companies deploy agents without losing control.
MODULE 8
FastAPI + Docker + AWS deployment, cost/latency budgets, tracing and monitoring for agent systems.
₹35,000complete program
Wondering how fees compare across providers? See AI course fees in India — ₹0 to ₹4 lakh compared.
Agentic AI is the practice of building systems where LLMs do not just answer questions but plan, use tools, and complete multi-step tasks autonomously. This agentic AI course teaches you to design and build such agents hands-on: tool calling, LangGraph state machines, CrewAI multi-agent teams, agentic RAG, human-in-the-loop patterns, evaluation, and production deployment.
The complete live program is ₹35,000 — 16 weeks of weekend live classes, deployed agent projects for your portfolio, lifetime recordings, and 100% placement support, with a 1-week money-back guarantee. Early-bird registrations get ₹32,000 pricing.
You need basic Python. The course covers the LLM foundations you need (APIs, prompting, RAG) before going deep into agents. If you are completely new to AI, the full AI course or the generative AI track may be a better starting point — book a free counselling call and we will honestly tell you which fits.
LangGraph (graph-based agent orchestration and state management), CrewAI (role-based multi-agent teams), LangChain tool calling, plus the model APIs — GPT-5, Claude, and Gemini. You also learn evaluation frameworks and guardrails, which are what separate demo agents from production agents.
Both exist — and the course is honest about it. Autonomous agents compound errors: a 95%-reliable step chained 10 times is only ~60% reliable. That is why production agent work is mostly about constrained workflows, tool design, evaluation, and human-in-the-loop checkpoints. Companies are hiring exactly for engineers who understand these constraints, and that is what we teach.
The AI automation course is for building business workflow automations with n8n and no-code/low-code tools plus LLMs. This agentic AI course is the developer track — writing Python code with LangGraph and CrewAI to build custom agents. If you are a developer or want to become an AI engineer, choose this one; if you want to automate business operations quickly, choose automation.
Roles hiring for these skills in 2026 include AI Engineer, GenAI Engineer, LLM Application Developer, and AI Solutions Engineer — with agent experience increasingly listed as a requirement. Indian packages typically range ₹12–40 LPA depending on experience. Agent-building portfolios stand out because few candidates have real, deployed examples.
Deployable, portfolio-grade projects: a research agent with tool calling and web access, an agentic RAG system over private documents, a multi-agent workflow built with CrewAI (e.g. a content or analysis pipeline), and a production-deployed agent with monitoring, guardrails and human-in-the-loop approval.
100% live online in weekend batches capped at 10 students, with lifetime access to recordings. You build alongside the instructor and get direct feedback on your agent designs — which matters more in agentic AI than in any other topic, because design mistakes are subtle.
The next batch starts July 12, 2026. Seats are limited to 10 per batch. Book a free counselling call to confirm availability and check fit for your background.
Limited Seats — Next Batch July 12, 2026
Join 100+ students already on the learning journey