Ask, share and contribute
Ask a question
- Enrolled in a course that uses this resource: use your instructor's support channel first. Your instructor sets the rules for collaboration and AI use.
- Studying independently: ask in GitHub Discussions, or open a "Learning question" issue for a problem with a lesson or exercise. Include the module, the command or notebook cell, the full error text, your Python version and what you expected. Never include passwords, personal data or student records.
- Accessibility barrier: use the accessibility reporting guide.
Questions that several learners share become improvements to the lessons, so asking helps the next person too.
Share strong work
The course may showcase learner projects that show careful evidence: a stated decision, a fair baseline, a preserved final test, and honest limits. A showcase entry needs:
- Written consent from the learner, using the exemplar consent template.
- Approval from the learner's instructor when the work was submitted for a course.
- Removal of names, student IDs, grades and any personal or confidential data.
- Reproducible commands and source attribution.
No learner work is published without all four. The completed capstone exemplar shows the standard of evidence; it was written for the course.
Contribute
Corrections, clearer explanations and new exercises are welcome. Read contributing and maintain and review. Every change keeps the module learning outcomes and the evaluation boundaries.