Free short course
Evaluation, red teaming and uncertainty
Build reference sets, calibrated rubrics, adversarial cases and useful release decisions.
This course is free in full: every module, knowledge check and the final task, with no sign-up.
Build reference sets, calibrated rubrics, adversarial cases and useful release decisions.
Understand basic percentages and the distinction between sources and claims. Each lesson includes a worked example, a practice task and an answer explanation. Allow about 12 minutes per lesson, five minutes for the knowledge check and 30 minutes for the final assignment. The reading is concise; the study time includes doing the exercises.
All scenarios are fictional. No paid subscription, specialist hardware or live AI integration is required to complete the written exercises. Advanced courses teach design and evaluation principles; they do not claim to provide a production implementation or professional accreditation.
By the end, you'll be able to…
- Create an evaluation report that explains failure types and limits.
- Keep evaluation cases independent enough to remain informative.
- Make a quality judgement inspectable.
- Compare outputs without letting presentation decide the winner.
- Look for failure conditions beyond the average case.
- Let a system stop when the evidence is insufficient.
What's in it
- Module 1: Evaluation, red teaming and uncertainty in practice
Create an evaluation report that explains failure types and limits.
- Finishing the course
One final task that puts the whole method to work on something real.