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A Python track built around work you can rerun: language fundamentals, files and errors, the NumPy and pandas stack, testing, and small automated projects.

Technology & engineering12 weeksBeginner → intermediate6–8 hours a weekUpdated 2026-10-14

A Python track built around work you can rerun: language fundamentals, files and errors, the NumPy and pandas stack, testing, and small automated projects.

This track runs on milestones you submit, not videos you watch. Each milestone names what you hand in, and the review is what turns it into a verified step on your record. Where an existing course or deep-dive guide already covers part of the track, it is linked from this page.

Tools the work uses

Python 3 and venvA reproducible interpreter and environment per project.
pandas, NumPy, MatplotlibTabular data, arrays and plots that state what they show.
pytestTests as a safety net, so a fix in one place cannot break another.
Jupyter and GitNotebooks for exploring, repositories for anything you keep.

Where this track leads

  • Python developer
  • Data analyst
  • Automation and QA engineer
  • Research software support

Where this track stands today

Nothing here is padded out to look finished. This is the honest state of the parts that are still being built.

Milestone briefs (12 weeks)Being written
Bioinformatics extensionLive — see the Python for Bioinformatics course

02/Other tracks

Start with the milestone, not the video.

Enrol once and every track on the platform becomes available — the milestones, the review and the certificate at the end.

Begin your internship How milestones work