Build your own AI assistant from scratch
Write your own AI assistant in Python, one short file at a time. From one API call to a multi-agent system that remembers you, runs commands safely, and keeps its own schedule.
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Intermediate is where production engineering starts. You’ve shipped a service or a script; now you want the patterns real teams use: evaluating RAG retrieval, wiring agents to tools, picking between async and sync, reading an OpenAPI spec, and shipping Docker + CI for something that isn’t trivial.
Curated by Param Harrison
Courses at this level assume you know the fundamentals and move fast. Less setup, more decisions. Real codebases, real trade-offs.
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Common questions
You’ve shipped at least one service or script to real users. You’re comfortable reading other people’s Python. You can read an API reference and figure out the rest. You want depth, not explanations of variables.
Depends on what you’re building. If RAG: RAG Fundamentals → Hybrid Search. If agents: AI Agents Fundamentals → AI Agent Design Patterns. If backend: Async Python Patterns → Twelve-Factor FastAPI.
Yes. The AI Bootcamp assumes intermediate comfort: you can write Python, you’ve used an LLM API once, you’re ready to wire together real systems.
Intermediate teaches the pattern. Advanced assumes you know the pattern and deep-dives the production gotchas. Evaluation harnesses, multi-agent coordination, observability in production.