Applied Tiny Machine Learning (TinyML) for Scale

Harvard University via edX Professional Certificate

edX Professional Certificate based on 0 ratings

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Overview

Tiny Machine Learning (Tiny ML) is a cutting-edge field that brings the transformative power of machine learning (ML) to the performance- and power-constrained domain of tiny devices and embedded systems. Successful deployment in this field requires intimate knowledge of applications, algorithms, hardware, and software. In this unique Professional Certificate program offered by Harvard University and Google ML, Data and AI Subject Matter experts, you will enhance your knowledge in the emerging field of Tiny ML, start applying the skills you...

Syllabus

Courses under this program:Course 1: Applications of TinyMLGet the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.Course 2: Deploying TinyMLLearn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. Before you know it, youll be implementing an entire TinyML application.Course 3: MLOps for Scaling TinyMLThis course introduces learners to Machine Learning Operations (MLOps) through the lens of TinyML (Tiny Machine Learning). Learners explore best practices to deploy, monitor, and maintain (tiny) Machine Learning models in production at scale.