Session by session
- Session 31 · Ask & understandWeek 16
Variables, lists and CSV rows
Evidence: a question, sketch or new vocabulary
- Session 32 · Build & designWeek 16
Read a small model-output log
Evidence: a design draft, dataset or build
- Session 33 · ImplementWeek 17
Count correct labels with conditions and loops
Evidence: a working version, explained once
- Session 34 · Test & improveWeek 17
Check missing rows and calculate percentages
Evidence: a test log with at least one failure
- Session 35 · Explain & reflectWeek 18
Explain the results using a short script
Evidence: an individual explanation
- Local Python
- prepared CSV
- no accounts
Twenty rows including a missing label; verify results by hand.
A model, an evaluation study or an AI-checking workflow.
Completion needs the artefact, an honest test log, an individual explanation and no open safety or privacy issue.
Projects in the same block
- RoboticsG08-P05
Parking Display Rover
A stationary rover display that reports proximity bands.
Sessions 21-25Builder and up - RoboticsG08-P06
Bluetooth-Controlled Car
A trainer-phone-controlled model car with a reliable stop path.
Sessions 26-30Builder and up - AIG08-P07
Python Data Detective
A simple Python evaluator for classifier predictions.
Sessions 31-35Builder and up - IntegratedG08-P08
AI Sorting Rover Station
A stationary AI-guided sorting station using rover hardware, not a roaming sorter.
Sessions 36-40Builder and up
For school leadersChoose a starting point.
Build from evidence.
Pick the classes and a plan. We map the timetable, kit and safety checks with you, then pilot one class first.
- Prospectus and class-wise plan
- Kit and readiness check
- Pilot one class first
- Evidence at every milestone
Let's plan your pilot.
Share a few details and we will send the right plan for your classes.