Agents is a comprehensive educational course repository that teaches agentic AI engineering through hands-on projects and code examples.
The course addresses the challenge of learning to build autonomous AI agents by providing a structured six-week curriculum that covers multiple frameworks and tools including OpenAI Agents SDK, CrewAI, LangGraph, Google ADK, Pydantic AI, and MCP. The approach combines conceptual guidance with practical Jupyter notebooks that learners work through sequentially, with setup instructions tailored for Windows, Mac, and Linux environments. The material emphasizes working with frontier AI models through API calls, though it acknowledges cost considerations and documents alternatives like DeepSeek and Ollama for those preferring lower-cost or free options.
This course suits developers who want structured, hands-on training in building AI agents rather than learning through scattered documentation. It works best for those willing to engage with API-based models and who have some programming foundation, though the README indicates it can accommodate learners with no prior programming background. The course includes supplemental resources such as video guides, an FAQ system, and direct instructor contact, positioning it as a guided learning path rather than a reference tool.
The project maintains active engagement with learners through multiple support channels including email contact, LinkedIn community building, and a YouTube channel with supplemental videos. The course underwent a comprehensive refresh with updated tools, models, and techniques, indicating responsiveness to the evolving agentic AI landscape. Documentation includes guides addressing common setup issues and API cost management, reflecting attention to practical learner concerns.
