Overview
ESE3600 Tiny Machine Learning (TinyML) is an exciting field at the intersection of embedded machine learning (ML) applications, algorithms, hardware, and software. TinyML differs from mainstream machine learning (e.g., server and cloud) in that it requires not only software expertise, but also embedded-hardware expertise.
This course emphasizes hands-on experience with ML training and deployment in tiny microcontroller-based devices. The course features application-based projects on a TinyML program kit that includes an Arm Cortex-M4 microcontroller with onboard sensors, a camera, and a breadboard with wires—enough to unlock capabilities such as image, sound, and gesture detection. Before you know it, you’ll be implementing an entire TinyML application.
The course will also feature real-world application case studies and a creative project that will help you examine the challenges facing real-world TinyML deployments.