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.
Deploying TinyML is an innovative and hands-on course that bridges the gap between computer science and electrical engineering, offering students a unique opportunity to dive into the world of Tiny Machine Learning (TinyML). This intermediate-level course, part of the TinyML Professional Certificate program from HarvardX, focuses on the practical aspects of deploying machine learning models on microcontroller-based devices.
Throughout this course, you'll gain invaluable experience in embedded systems, machine learning training, and deployment using TensorFlow Lite for Microcontrollers. You'll work with a TinyML Program Kit, which includes an Arduino board equipped with onboard sensors and an ARM Cortex-M4 microcontroller, allowing you to build exciting applications in image recognition, audio processing, and gesture detection.
This course is ideal for intermediate-level learners with a background in computer science or electrical engineering who want to explore the exciting field of TinyML. It's perfect for developers, engineers, and hobbyists interested in implementing machine learning on resource-constrained devices and creating innovative IoT applications.
The skills acquired in this course have numerous real-world applications across various industries. Learners can apply their knowledge to develop:
These skills are highly valuable in the rapidly growing fields of IoT, edge computing, and embedded AI, opening up numerous career opportunities and possibilities for innovation.
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