In this course, students will study the emerging field of tiny machine learning (tinyML). This field is at the intersection of machine learning (ML) applications and embedded devices/microcontrollers. It requires both software and embedded-hardware knowledge. More specifically, students will follow a hands-on learning approach with training and optimizing ML models in such ways that they are deployable onto tiny microcontrollers. The course will involve work with an Nano 33BLE sense microcontroller.