Python Foundations
You already program. This module rewires how you think in Python so the rest of the path feels natural: the data model, idioms, concurrency, and the typing discipline that keeps production AI code honest.
Start the first lesson →Environments, Packaging & Tooling
Virtual environments, dependency pinning, and the modern toolchain (uv, ruff, pytest) that professional Python rests on.
Not started2The Data Model & Dunder Methods
Why everything is an object and how the special methods (__len__, __iter__, __eq__ …) let your own types plug into the language.
Not started3Idioms, Comprehensions & Iterators
Comprehensions, unpacking, and the iterator protocol. Write Python that reads like Python instead of translated Java.
Not started4Generators & Lazy Evaluation
Stream data instead of materializing it. yield, generator pipelines, and why laziness matters when the data does not fit in memory.
Not started5Functions, Closures & Decorators
First-class functions, closures, and decorators — the machinery behind caching, retries, and most framework 'magic'.
Not started6Classes, Dataclasses & Protocols
Modeling with classes without over-engineering: dataclasses, composition over inheritance, and structural typing via Protocol.
Not started7Concurrency, Async & the GIL
Threads vs. processes vs. asyncio, the GIL, and where each one actually helps when you are serving models.
Not started8Typing & Robust Code
Type hints, generics, protocols, and how static typing catches the bugs that surface at 3am in production.
Not started9Testing, Debugging & Profiling
pytest patterns, fixtures, and finding the slow line with a profiler instead of guessing. Confidence to change code fast.
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