Foundations of TinyML
Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.
Applications Of TinyML
Get 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.
Deploying TinyML
Learn 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, you’ll be implementing an entire TinyML application.
MLOps for Scaling TinyML
This 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.
Introduction to Embedded Machine Learning
This course will give you a broad overview of how machine learning works, how to train neural networks, and how to deploy those networks to microcontrollers using the Edge Impulse Platform.
Computer Vision with Embedded Machine Learning
This course, offered by a partnership among Edge Impulse, OpenMV, Seeed Studio, and the TinyML Foundation, will give you an understanding of how deep learning with neural networks can be used to classify images and detect objects in images and videos.