Harvard CS249r: Tiny Machine Learning (TinyML)
Fall 2020
Derek Bok Center Distinction in Teaching Award
Harvard CS249r: Tiny Machine Learning (TinyML)
Fall 2020
Course Overview
The explosive growth in machine learning and the ease of use of platforms like TensorFlow (TF) make it an indispensable topic of study for the modern computer science student. At the same time, the pervasiveness of ultra-low power embedded devices, coupled with the introduction of embedded machine learning frameworks like TensorFlow Lite for Microcontrollers will enable the mass proliferation of AI powered IoT devices. As such we have designed an introductory course on Applied AI at the intersection of Machine Learning and Embedded IoT Devices. We provide background on both topics and then dive into the unique challenges faced at that intersection point with hands-on assignments using TensorFlow, Google Colab, and Arduino.
My Roles
- Co-designed a new 40 student Applied AI course on the emerging field of Tiny Machine Learning (deploying machine learning onto microcontrollers for machine learning at the extreme edge)
- Designed and gave lectures for the introduction to machine learning section of the course
- Co-developed hands-on project-based assignments training TinyML models with Google Colab and deploying on Arduinos
- Mentored student teams pursuing research-based final projects
