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Build AI Agents CrewAI, LangGraph, OpenAI SDK, Autogen, MCP
Published 6/2026
Created by Deesa Technologies
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 77 Lectures ( 23h 50m ) | Size: 15.7 GB
End-to-end AI agent bootcamp - from your first LLM call to multi-agent systems you can deploy at work
What you'll learn
⚡ LLM fundamentals: tokens, cost, latency, capabilities & limitations
⚡ Prompt engineering that controls output (JSON, classification, extraction)
⚡ Agent design patterns: tool use, multi-step reasoning, failure modes
⚡ OpenAI Agents SDK for research copilots, meeting notes → action items, support bots
⚡ CrewAI multi-agent orchestration for software teams, product launches & hiring
⚡ LangGraph stateful workflows with human-in-the-loop approval
⚡ AutoGen collaborative code review and problem-solving agents
⚡ MCP integration for databases, PDFs, and live market data
⚡ Guardrails to prevent unsafe or unreliable AI outputs
⚡ Observability: logging, tracing, failure simulation & quality evaluation
⚡ Deployment: FastAPI, webhooks, cost optimization
Requirements
❗ Basic Python knowledge
❗ Curiosity and willingness to build - no ML PhD required
Description
Stop watching AI demos. Start building AI systems companies actually ship.
This hands-on bootcamp takes you from your first LLM API call toproduction-grade multi-agent systems - using the tools shaping AI engineering today:OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, and MCP.
You won't just learn theory. You'lldesign, build, debug, secure, and deploy real AI applications in Python.
What you'll build
✨ 29 exciting AI projects that we will design from scratch
✨ AI research assistant, email generator & chatbot (Module 0)
✨ Prompt playground, JSON formatter & email classifier
✨ Resume analyzer, data extractor & SQL assistant
✨ Web search agent & multi-step task agent
✨ OpenAI SDK: research copilot, meeting notes → action items, support bot
✨CrewAI flagship: AI software engineering team (Developer → Reviewer → Tester)
✨ LangGraph customer support & human-in-the-loop approval workflows
✨ AutoGen collaborative code review & problem-solving agents
✨ MCP: internal data assistant, knowledge base agent, trading simulation
✨ Debug dashboard, failure simulator & output evaluator
✨GitHub AI PR code reviewer (FastAPI + webhooks)
This course doesn't just teach you how to design and build AI systems - it also shows you how and when AI fails, and what to do about it. It's a production-ready bootcamp that takes you all the way to deployment, including a GitHub AI PR reviewer you can run in real time and watch interact with live pull requests.By Deesa Technologies - production-focused courses built by engineers who ship real systems.
Enroll now and build your first AI agent in Module 0.
Who this course is for
⭐ Python developers who want to move into AI engineering
⭐ Software engineers building internal AI tools at work
⭐ Data professionals who need practical agent workflows, not theory-only content
⭐ Career switchers targeting AI Engineer / ML Engineer / Agent Developer roles
⭐ Anyone tired of copy-paste ChatGPT tutorials who wants real system design skills
Homepage
https://www.udemy.com/course/build-ai-agents-crewai-langgraph-openai-sdk-autogen-mcpRecommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
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