Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
16 Hour(s) 49 Minute(s)
Language
English
Taught by
Ed Donner, Ligency
Rating
Course Overview
Master AI Agents in 30 days: build 8 real-world projects with OpenAI Agents SDK, CrewAI, LangGraph, AutoGen and MCP.
2025 is the year that Agents enter the workforce. This is nothing short of a watershed moment for Artificial Intelligence. It has never been more important to be an expert with Agentic AI. And that is precisely the goal of this course: to equip you with the skills and expertise to design, build and deploy Autonomous AI Agents, opening up new career and commercial opportunities.
This is an intensive 6-week program to master Agentic AI. We start by building foundational expertise, connecting LLMs using proven design patterns. Then, each week, we upskill with new frameworks: OpenAI Agents SDK, CrewAI, LangGraph and Autogen. The course culminates with a full week on the remarkable opportunities opened up by MCP.
Above all, this is a hands-on course. I’m a big believer that the best way to learn is by DOING. So please prepare to roll up your sleeves! We’ll build 8 real-world projects; some are astonishing, some are intriguing, and some are quite surreal. But one thing’s for sure: all are powerful demonstrations of Agentic AI’s potential to utterly transform the business landscape.
So come join me on this comprehensive 6-week journey. By the end, you will have mastered Agentic AI. You will have expertise in all the major frameworks. You’ll be well-versed in the strengths and traps of Agentic AI. You’ll confidently unleash Autonomous Agents to solve real-world commercial problems. And along the way, you’ll have had a whole lot of fun with the astounding, groundbreaking technology that is Agentic AI.
Course Content
- 6 section(s)
- 129 lecture(s)
- Section 1 Week 1
- Section 2 Week 2
- Section 3 Week 3
- Section 4 Week 4
- Section 5 Week 5
- Section 6 Week 6 - MCP
What You’ll Learn
- Project 1: Career Digital Twin. Build and deploy your own Agent to represent you to potential future employers.
- Project 2: SDR Agent. An instant business application: create Sales Representatives that craft and send professional emails .
- Project 3: Deep Research. Make your own version of the essential Agentic use case: a team of Agents that carry out extensive research on any topic you choose.
- Project 4: Build a Stock Picker Agent in minutes with CrewAI—automate your search for investment gems!
- Project 5: Deploy your own 4-Agent Engineering Team—manage, build, and test software apps with CrewAI and Coder Agents in Docker!
- Project 6: Build your own version of OpenAI’s Operator Agent—your Sidekick works with you inside your browser via LangGraph!
- Project 7: Agent Creator—an Agent that builds and launches new Agents using AutoGen, unlocking endless AI possibilities!
- Project 8: Capstone—build a Trading Floor with 4 Agents making autonomous trades, powered by 6 MCP servers and 44 tools!
Skills covered in this course
Reviews
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RRasheed Adesokan
Thanks Ed for taking us through this journey. I can't wait to utilise the knowledge you thought me in this course in a real-world project. On a final note, I will be looking forward to your next course. I am on the other two by the way.
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UUpasana
Excellent course , makes clear of every fundamental of Agentic AI development. Detailed insight of major frameworks in use and design patterns
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SSameer Thomare
Completed an intensive 6-week Agentic AI Engineering Udemy course led by @Ed-Donner, featuring 8 real-world projects that develop practical skills using leading agentic frameworks (OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, MCP) and LLM APIs (OpenAI, Google Gemini, Meta Llama, Anthropic Claude, Deepseek, Groq, etc). The program also briefly covered other ancillary tools including Cursor, Huggingface, Serper, Sendgrid, Pushover, Brave Search API, Playwright and Polygon/Massive IO, enabling deployment and orchestration of autonomous agents in contemporary AI workflows. Highly recommended for professionals seeking hands-on mastery in agentic AI systems and multi-agent engineering.
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TThiyagarajan Pl
The tutorial is great and provides various perspectives on AI frameworks. However, the MCP chapter was covered too quickly, and certain aspects of the final capstone projects were not clearly explained. Everything else was well done.
