Master AI Agents in 30 days: build 8 real-world projects with OpenAI Agents SDK, CrewAI, LangGraph, AutoGen and MCP.
InstructorEd DonnerComidoc has tracked 2 coupons for this course since 2026, last checked 4 months, 3 days ago.
| Coupon code | Discount | Added | Status | Lifetime |
|---|---|---|---|---|
| AI_APR26 | $14.99 | Expired | 27d 7h | |
| AI_MAR26 | $14.99 | Expired | 28d 3h |
The curriculum provides exposure to several major orchestration methods, including OpenAI Agents SDK, CrewAI, LangGraph, and Microsoft AutoGen.
A dedicated section covers the Model Context Protocol (MCP) architecture, including host/client/server relationships and building custom servers.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This notebook introduces the Autonomous Alpha Agents capstone project, detailing an equity trading simulation powered by various MCP servers and tools.
This frame displays a Jupyter Notebook environment featuring Python code that imports LangGraph and Pydantic modules to define structured output schemas for AI agents.
This instructional slide explains that CrewAI projects are UV projects, showing the command to install the tool, create a new project named my_crew, and run it.
This instructional slide defines core concepts for building AI systems, detailing the specific roles of Agents, Tasks, and Crews within autonomous workflows.
The track utilizes practical projects, such as building a trading floor and research agents, to bridge theory and application.
As the curriculum progresses into complex orchestration, some learners report that the instruction moves too quickly through technical syntax and implementation details.
As the curriculum progresses into complex orchestration, some learners report that the instruction moves too quickly through technical syntax and implementation details. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
One signal indicates that specific API calls within a project may fail, and some tools like Cursor may require manual updates to match the current environment.
The content aligns well with those seeking agentic expertise, though it may be challenging for absolute beginners. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
