A live, mentor-led AI agent development course for developers, AI engineers and automation professionals — build multi-agent systems with LangGraph, CrewAI and AutoGen, and ship them to production.
Sixteen weeks from first principles to a deployed multi-agent system. Every module is hands-on — you build, break and ship agents rather than watch them being demonstrated.
Every competency mapped to what teams hiring agent engineers in India actually test for in interviews.
Every tool chosen for real-world relevance — the same stack that powers production AI at product companies hiring agent engineers.
Real agent engineering in real production environments — from a single-tool agent to an autonomous multi-agent system under guardrails.
Build an agent that decides when to call a web-search tool, reads the results and returns a cited answer instead of hallucinating one.
Ingest a document corpus, chunk and embed it, then answer grounded questions with citations and an explicit refusal when context is missing.
Turn unstructured documents into validated JSON using structured output modes, with retry logic when the model returns malformed data.
Get expert guidance and mentorship on every project, from engineers who ship production AI.
Nine structured objectives from agent foundations to production agent ops — select any node to explore it.
Understand what separates an agent from a chatbot: autonomy, goal-seeking, feedback loops, and the ReAct, Plan-and-Execute and Reflexion patterns.
Five phases. One transformation — from your first agent to a placed career in AI engineering.
Where autonomous agents are actually deployed today — and the capability each pattern depends on.
Agents that read a diff, run the test suite, flag regressions and open a PR comment with a suggested patch — escalating to a human when confidence is low.
Tool use · Code execution · Guardrails
Retrieval over policy documents and ticket history to draft grounded replies, auto-resolve routine issues and route the rest with full context attached.
RAG · Classification · Escalation logic
Multi-agent crews that gather filings, cross-check figures against source documents and produce cited summaries an analyst can audit line by line.
Multi-agent · Citation tracking
Agents that structure unstructured notes into validated schemas, with human-in-the-loop approval gates before anything enters a record system.
Structured output · Approval gates
Automated product enrichment, category assignment and description generation across large catalogues, with quality scoring before publication.
Batch pipelines · Evaluation
Agents that search across wikis, tickets and databases to answer employee questions, honouring per-user access permissions at retrieval time.
Hybrid search · Access control
Or ₹4,167/month for 12 months on EMI.
This agentic AI track is delivered inside Skillfyme’s flagship generative AI and agentic AI course, alongside the LLM, RAG and MLOps foundations that production agents depend on.
Who stands behind your certificate.
IIT Patna at a glanceRecognises Vishlesan i-Hub as an NIC (National Innovation Centre), part of India's national AI mission.
Hosted byOne of India's top engineering institutes, with incubators and innovation hubs that bridge academia and industry.
Research hubAdvances AI in speech, video and text analytics for health, education and security.
What you receiveIssued jointly by Skillfyme and Vishlesan i-Hub, carrying the credibility of an IIT institution.
An agentic AI course teaches you to build AI systems that pursue goals autonomously — planning, calling tools, using memory and correcting themselves — rather than answering a single prompt. Skillfyme's programme is built for developers, AI engineers and automation professionals who can already write Python and want to ship production agents with LangGraph, CrewAI and AutoGen.
