Learning Tracks
Many tracks and dozens of sub-tracks. Every track starts with a free intro lesson.
Build intelligent systems that think and act.
Three sub-tracks. Start with the tier that matches your background.
Use visual, drag-and-drop platforms (n8n, Zapier, Make.com, Voiceflow) to wire together LLM calls, tools, and logic into fully functional AI agents. Includes n8n error handling + retry patterns, the honest 'when not to use no-code' lesson, and job readiness for AI automation roles.
Use low-code platforms (LangFlow, Flowise, Dify, Relevance AI) to build agents with visual UIs. Includes self-hosting Flowise via Docker to a public VPS, a deep RAG pipeline design lesson (chunking + embeddings + vector stores + precision@5 evals), and job readiness.
Use Python frameworks (LangChain v0.2+ / LangGraph / LlamaIndex / CrewAI) and raw SDKs (Anthropic, OpenAI) to build production-grade AI agents. Includes the Model Context Protocol, multi-agent orchestration patterns, a formal passion project with three brief options, and job readiness for AI / agent engineer roles.