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01
Foundations
The shortest honest route from Python to shipping something that uses an LLM and doesn't fall over.
6 lessons · ~40 hours
0 / 6
- 01
Python for AI engineers
The parts of Python that bite you when calling models in production.
- 02
LLM fundamentals
Tokens, temperature, context windows, cost. What matters and what doesn't.
- 03
Prompt engineering
Structured output, few-shot patterns, and injection as a security problem.
- 04
Embeddings and vector search
How text becomes vectors, and where the abstraction leaks.
- 05
Retrieval-augmented generation
A full RAG pipeline end to end, then where each stage breaks.
- 06
Your first agent
Tools, the reasoning loop, and termination — before any framework.
Next
Production Systems