# Mission: Python

## Why

Learn Python to analyze real datasets — load, clean, explore, and visualize data
(starting with finance-flavored data) instead of reading about it secondhand.
Builder track: unlike `ai-finance` (concepts only, no code), this course produces
runnable scripts.

## Success looks like

- Write and run a Python script from scratch without looking up basic syntax
- Load a real CSV/dataset with pandas, inspect it, and answer questions about it
  (filter, group, aggregate)
- Clean messy data: handle missing values, wrong types, duplicates
- Produce a chart from a dataset that answers a specific question
- Read someone else's data-analysis script and know what each part does

## Constraints

- Already comfortable with programming concepts (variables, loops, functions,
  conditionals) from another language — don't re-teach concepts, teach Python's
  syntax and idioms for them
- Lessons short enough to finish in one sitting
- Bias toward real datasets over toy examples as soon as the fundamentals allow it

## Out of scope

- Building/training ML models (that's a future mission if this one lands)
- Web backends, packaging/distribution, async — anything not in service of data analysis
- Deep language internals (metaclasses, descriptors, GIL mechanics)