Agentic AI · Live online

Agentic AI Course Online — Build Agents That Finish the Job Without Going Rogue

An agent demo takes an hour. An agent a business can let loose on real customers, real tickets or real invoices takes careful engineering: clear tools, controlled state, limits, approvals and evaluation. This course teaches both halves, live and online.

Get course details on WhatsAppWhat you'll build
Duration
6 months
Live online classes
336 hrs
Deployed projects
5
Total fee, paid monthly
₹34,994

Short answer: AIKranti teaches Agentic AI in months 4–5 of a 6-month live online AI Engineer course, using LangChain, LangGraph, tool calling, multi-agent patterns and the Model Context Protocol (MCP), followed by deployment on AWS. It builds on Python, ML, LLM and RAG modules taught earlier. Fee ₹34,994, paid month by month.

From a single tool call to a multi-agent system

  1. Step 1

    Tool calling & the ReAct loop

    • Function schemas
    • Reason → act → observe
    • Handling tool errors
  2. Step 2

    Stateful agents with LangGraph

    • Graphs, nodes & edges
    • Shared state
    • Checkpoints & memory
  3. Step 3

    Agentic RAG

    • Agents that decide when to retrieve
    • Query rewriting
    • Self-checking answers
  4. Step 4

    Multi-agent collaboration

    • Supervisor & worker agents
    • Hand-offs
    • Human-in-the-loop approvals
  5. Step 5

    MCP & production hardening

    • Model Context Protocol servers
    • Iteration limits & cost caps
    • Tracing & evaluation
    • AWS deployment

The capstone agent project

A LangGraph system in which several agents, each with its own tools and responsibilities, work through a realistic business task over shared state. It includes tracing, evaluation runs, iteration limits and a live deployment. It's the hardest project in the course, and usually the one interviewers ask about most.

Where agents are being used right now

  • Customer support: look up, decide, act, escalate
  • IT operations: read alerts, run runbook steps with approval
  • Finance back office: invoice → validate → exception report
  • Sales: research prospects and draft outreach

See how this maps to support engineers and SAP consultants.

Where Agentic AI fits in the 6 months

  1. Months 1–2

    Python & software foundations

    • Python from zero (OOP, files, generators)
    • Linux, Bash & Git
    • FastAPI & REST APIs
    • Pydantic & Postman
    • 500+ graded coding exercises
  2. Month 3

    Machine learning, deep learning & NLP

    • Core ML algorithms & evaluation
    • Neural networks
    • NLP pipeline, Word2Vec
    • Transformers & attention
  3. Months 3–4

    Generative AI & LLMs

    • Prompt engineering
    • OpenAI & Hugging Face models
    • Embeddings & vector databases
    • RAG over private documents
    • Fine-tuning & evaluation
  4. Months 4–5

    Agentic AI

    • LangChain & LangGraph
    • ReAct & tool calling
    • Multi-agent systems
    • Agentic RAG
    • Model Context Protocol (MCP)
  5. Months 5–6

    MLOps, AWS & getting hired

    • Docker, Kubernetes, CI/CD
    • AWS: EC2, Lambda, S3, Bedrock, SageMaker
    • Monitoring & cost control
    • Resume, LinkedIn & GitHub portfolio
    • Weekly mock interviews

Full module-by-module breakdown: AI Engineer course syllabus.

Pay after you learn

No big upfront fee: pay after every 30 days of classes

  1. Start₹1,999
  2. Day 30₹6,999
  3. Day 60₹6,999
  4. Day 90₹6,999
  5. Day 120₹6,999
  6. Day 150₹4,999
  7. Day 180₹0
  • ₹1,999 to reserve your seat
  • No loan, EMI or interest
  • Stop at any month end

Total ₹34,994See when you pay →

Agentic AI course: FAQs

What is Agentic AI, in simple terms?

Agentic AI means systems where a language model decides what steps to take toward a goal: which tool to call, what to do with the result, and when to stop. A chatbot answers a question. An agent can look up an order, check a policy, raise a refund request and update the ticket.

Can a beginner learn Agentic AI?

Yes, in sequence. Agents are built on Python, APIs, LLMs and RAG, so the course teaches those first. Jumping straight to agent frameworks tends to produce demos that break on the first unexpected input.

Which frameworks does the Agentic AI module use?

LangChain and LangGraph for building agents, the Model Context Protocol (MCP) for connecting tools, and AWS for deployment, along with tracing and evaluation practices.

What makes AI agents hard to build in production?

Reliability. Agents can loop, call tools with wrong arguments, act on bad data or run up token costs. The course covers state management, iteration limits, human approval steps, tracing and evaluation.

Are there Agentic AI jobs in India?

Yes, and growing. Product companies, GCCs and IT services firms are building agents for customer support, IT operations, finance and back-office automation.

Reserve a seat in the October 2026 batch

Register for ₹1,999. Every other instalment is paid only after that month has been taught.

Get course details on WhatsApp