You already have a task laid out along the cycle, a climb up the "prompt → context → agents" ladder, and an evaluation plan. One thing is missing — a run of your own.
Picture an evening after which you've shifted a model's weights with your own hands. No paid cloud, on a free GPU in the browser or on your own hardware.
What do you want to see in the "before" and "after" comparison to believe that it worked?
Getting it wrong is fine: it is part of learning. Guessing first helps the answer stick later, and the answer itself comes after the explanation.
Copy your personal prompt and paste it into your agent's learn mode — it picks up your context and takes you forward.
Honestly: with AI it feels like you can do more than you can without it. After practice, check yourself without AI. (Bastani et al., PNAS 2025)
Explains the material using the course method.
Show your practice result
The module is done. Post what you built in the course topic — module number in the first line — and reply to two fellow learners: what worked, what you would try differently. Your work lives in the group, not with us. No keys, passwords or other people’s data.
To the course topic ↗