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Data science educators & enablement teamsTeach runnable lessons

Sharing browser notebooks

Help educators and data teams share runnable notebooks that keep code, results, and explanation in one GPDoc file.

Launch a browser notebook

Typical blockers

  • Classroom labs require virtual machines or local Python installs.
  • Workshop participants lose time debugging setup issues.
  • Sharing outputs means emailing static notebooks or screenshots.

How GPDoc solves it

  • Browser runtimes for Python, TypeScript, and SQL keep lessons close to the file.
  • Dataset caching can keep prepared lessons usable when connectivity is limited.
  • Git review workflows capture feedback, rubric notes, and grading history.
  • One-click publishing generates HTML embeds, Markdown, or .ipynb files for LMS uploads.

Bring your own libraries

Pin dependencies in workspace.config.json; GPDoc caches packages per workspace so every student runs the same stack.

Suggested rollout

Organize notebooks by module, week, or cohort. Attach learning objectives and success metrics in metadata.

Include intro markdown, starter code, and evaluation cells so instructors stay consistent across sessions.

Students fork or branch the notebook, run it in the browser, and submit via pull request for feedback.

Capture final HTML/PDF for accreditation while keeping the runnable version available for demos.

KPIs to watch

  • Classroom setup time per cohort
  • Successful execution rate on first try
  • Instructor review turnaround

Extend it

Pair GPDoc notebooks with embedded slides and docs to create full blended-learning journeys.

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