AI & TinyML / TEACHING GUIDE
Bring TinyML onto the workbench
See, hear, and respond with a small embedded system.
A teaching sequence
- Onboard the board
The February–March agendas begin with Arduino IDE setup and checks of blink, microphone, camera, and Wi-Fi. Confirm the exact board and expansion hardware before following a kit tutorial.
- Explore a model
Use a supported camera or audio model. Identify its inputs, predicted classes, and hardware requirements. Distinguish using a pretrained model from training your own.
- Connect prediction to action
Have a classification trigger a clear response such as an indicator or a controlled servo. Test the actuator separately before integrating it.
- Explain the limits
Record when the model is uncertain or wrong. Discuss light, background, sound, and how data collection changes performance.
Source & adaptation
Teaching outline combines the daily agendas and the instructor’s confirmed curriculum. It is not a complete wiring or code tutorial.
Use this as a planning guide and adapt it to your equipment, students, and timetable.
Find handouts and platform resources →
Original AIM teaching material may be adapted with attribution to David McLoda. Reuse details