# Sources and version notes

Reviewed 14 October 2026. Course prose, examples, datasets and SVG diagrams are original. These primary sources ground API behavior and provide further reading; they are not copied chapters. Stable documentation changes over time, so the actual execution versions are recorded separately in `VERIFICATION.md`.

## Scope and lab

- [Public Python for AI and Data course page](https://aabhaai.com/courses/python-ai-data/): inspected in the cloud browser; planned beginner foundation followed by an applied data project. No enrolment change was made.
- [Aabha Code Lab](https://lab.aabhaai.com/): inspected and exercised in the cloud browser. Profiles expose Python, Data and Charts separately. Browser storage is not a substitute for downloaded work.

## Python

- [Python tutorial](https://docs.python.org/3/tutorial/): language reference path for learners
- [Numbers and text](https://docs.python.org/3/tutorial/introduction.html): expressions, strings and indexing
- [Control flow and functions](https://docs.python.org/3/tutorial/controlflow.html): branches, loops, function definitions and parameter behavior
- [Data structures](https://docs.python.org/3/tutorial/datastructures.html): containers and collection operations
- [Modules](https://docs.python.org/3/tutorial/modules.html): import structure and module use
- [Input and output](https://docs.python.org/3/tutorial/inputoutput.html): files, formatting and context managers
- [Errors and exceptions](https://docs.python.org/3/tutorial/errors.html): explicit exception handling
- [Floating-point limits](https://docs.python.org/3/tutorial/floatingpoint.html): representation and approximate comparisons
- [CSV module](https://docs.python.org/3/library/csv.html): quoting-aware readers and writers, newline handling
- [unittest](https://docs.python.org/3/library/unittest.html): repeatable tests using the standard library
- [venv](https://docs.python.org/3/library/venv.html): isolated local environments and direct interpreter invocation without activation

## Data and charts

- [NumPy beginner guide](https://numpy.org/doc/stable/user/absolute_beginners.html): array shape, dtype, indexing and reductions
- [NumPy copies and views](https://numpy.org/doc/stable/user/basics.copies.html): shared memory and explicit copies
- [pandas introductory tutorials](https://pandas.pydata.org/docs/getting_started/intro_tutorials/index.html): tabular selection, grouping and summaries
- [pandas read_csv](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html): string ingestion and missing-value options
- [pandas to_datetime](https://pandas.pydata.org/docs/reference/api/pandas.to_datetime.html): date conversion and coercion
- [pandas copy-on-write guide](https://pandas.pydata.org/docs/user_guide/copy_on_write.html): why ambiguous chained assignment is avoided
- [Matplotlib quick start](https://matplotlib.org/stable/users/explain/quick_start.html): Figure/Axes, plotting and output

## What the links do not establish

Documentation describes APIs, not this course's learning effectiveness. Local tests and selected browser tests provide specific compatibility evidence, not a guarantee across every device, package combination or future release. The course has not been piloted with learners. No claim of external accreditation, certification or live publication is made.