Go beyond basic prompt engineering. In 6 intensive weeks, go from zero to designing, orchestrating, and deploying autonomous multi-agent systems — with LangGraph, CrewAI, AutoGen, RAG, and MCP tools woven into every module.
Move from static chatbots to multi-agent workflows that perceive, reason, call tools, execute code, and ship to production.
Master the Perceive → Reason → Act loop, ReAct patterns, function calling, and structured outputs step by step.
Coordinate specialized agent teams using LangGraph, CrewAI, and AutoGen with human-in-the-loop guardrails.
Equip agents with long-term vector memory (Pinecone, ChromaDB) and self-correcting retrieval pipelines.
Deploy live FastAPI agent endpoints and graduate with an Uncoder + IBM verified specialization certificate.
Every module combines foundational agent architectures with production frameworks used by modern AI engineering teams.
Graduate with deployed, production-ready multi-agent systems on your GitHub that recruiters can test live.
Upload complex PDFs and docs. The agent grades retrieved context, rewrites ambiguous queries, falls back to live web search when needed, and answers with verified citations.
Upload any raw CSV dataset. The agent inspects schemas, writes and executes Pandas code inside a secure E2B sandbox, generates visual charts, and delivers an executive report.
A coordinated 4-agent crew (Planner, Web Researcher, Writer/Coder, and QA Critic) with Human-in-the-Loop approval, streaming SSE updates, and live cloud deployment.
Hands-on experience with the exact orchestration frameworks, vector databases, and observability tools used by top AI teams.
Autonomous AI engineering is the highest-leverage specialization in software today. Here are the roles this program prepares you for.
Design and orchestrate autonomous multi-agent systems using LangGraph, CrewAI, and MCP for enterprise automation.
Build production LLM applications, tool-calling pipelines, and streaming AI backends with FastAPI and Python.
Architect enterprise knowledge retrieval systems using vector databases, hybrid search, and self-reflective RAG.
Ship end-to-end AI SaaS products integrating autonomous agent backends with reactive modern web interfaces.
Ensure autonomous agents remain safe, accurate, and cost-effective in production using guardrails and tracing.
Lead the transition from manual workflows to multi-agent enterprise automation across engineering and ops teams.
Everything you need to know about the Agentic AI Specialization Workshop.
This is a 6-week intensive live program featuring mentor-led classes, guided coding labs, multi-agent architecture assignments, and a production capstone deployment.
No advanced math or prior ML experience is required. Basic familiarity with Python is enough — we teach LLMs, tool calling, RAG, and multi-agent frameworks from the ground up.
You will work hands-on with LangGraph, CrewAI, Microsoft AutoGen, LangChain, Model Context Protocol (MCP), Pinecone, ChromaDB, E2B Code Sandboxes, LangSmith, and FastAPI.
Yes! Every module includes a live build lab, and you will graduate with 6+ working agents and a cloud-deployed multi-agent capstone application on your GitHub portfolio.
Yes. Upon completing the program and capstone project, you will earn a verifiable Uncoder Agentic AI Specialization Certificate along with placement and interview preparation support.
Whether you're a college student, fresher, or working developer — if you know basic Python, we'll help you build and ship production AI agents in 6 weeks.
⚡ Limited seats per cohort — early applicants & freshers get priority!