Master new skills with our 21-day learning paths, broken into easy 5-minute daily lessons.
Start your journey for free.
Master new skills with our 21-day learning paths, broken into easy 5-minute daily lessons.
Start your journey for free.
Run AI on microcontrollers. Train and deploy TensorFlow Lite models to Arduino and ESP32 for voice, gesture, and vision recognition.
AI is moving to the edge. TinyML allows machine learning models to run on battery-powered microcontrollers with kilobytes of RAM. This course teaches you to train models using Edge Impulse or TensorFlow, optimize them (quantization) for small devices, and deploy them to Arduino/ESP32. You will build projects like keyword spotting (voice control), gesture recognition (magic wand), and anomaly detection for predictive maintenance.
Estimated completion time: 21 lessons • Self-paced learning • Lifetime access
Arduino Nano 33 BLE Sense is recommended.
Understanding neural nets helps, tools simplify it.
Surprisingly fast for specific tasks (DSP).
No, inference happens 100% offline on chip.
3 recommended paths based on what you're learning
Top performers in Edge AI (TinyML) often move into Solutions Consultant. See why.
API Basics gives your Edge AI (TinyML) skills a serious edge. Worth the 5-minute intro.
Work faster, not harder. ChatGPT + Notion AI was built to learn anything 10x faster.