Awesome Testing
Guided course + reference

How Machines Learn materials

Every lesson moves through a concise mechanism, experiment, written evidence brief, and checkpoint. Drafts stay in your browser and can be exported as Markdown; the complete theory chapter remains available afterward as optional reference.

Prior knowledge
Comfort reading simple equations helps. The course introduces the calculus it uses.
Study time
2–3 hours guided · about 3¼ hours of optional deep dives
By the end
Trace how a supervised model turns error into parameter updates, then diagnose where training evidence can mislead you.

8

lesson experiments

8

exportable worksheets

8

reference chapters

8

knowledge checks