What you will learn
- Fundamentals of machine learning and embedded devices.
- How to gather data effectively for machine learning.
- How to train and deploy tiny machine learning models.
- How to optimize machine learning models for resource-constrained devices.
- How to conceive and design your own tiny machine learning application.
- How to program in TensorFlow Lite for Microcontrollers, using an ARM Cortex-M4
In this exciting Professional Certificate program offered by Harvard University and Google TensorFlow, you will learn about the emerging field of Tiny Machine Learning (TinyML), its real-world applications, and the future possibilities of this transformative technology.
TinyML is a cutting-edge field that brings the transformative power of machine learning (ML) to the performance- and power-constrained domain of embedded systems. Successful deployment in this field requires intimate knowledge of applications, algorithms, hardware, and software.
The program will emphasize hands-on experience with training and deploying machine learning into tiny embedded devices. This series of courses features projects based on a TinyML Program Kit that includes an Arduino board with onboard sensors and an ARM Cortex-M4 microcontroller. To ensure you hit the road running, the kit also comes equipped with a camera. The TinyML Program Kit has everything you need to unlock your imagination and build applications around image recognition, audio processing, and gesture detection. Before you know it, you’ll be implementing an entire tiny machine learning application.
This first-of-its-kind program combines computer science with engineering to feature real-world application case studies that examine the challenges facing TinyML deployments.
This program is a collaboration between expert faculty at Harvard’s John A. Paulson School of Engineering and Applied Sciences (SEAS) and innovative members of Google’s TensorFlow team.
Courses in this program
HarvardX's Tiny Machine Learning (TinyML) Professional Certificate
- 2–4 hours per week, for 6 weeks
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.
- 2–4 hours per week, for 5 weeks
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.
- There are hundreds of billions of microcontrollers today, and an increasing desire to deploy machine learning models on these devices through TinyML. Learners who complete this program will be prepared to dive into this fast-growing field.
- Learners will have a fundamental understanding of TinyML applications and use cases and gain hands-on experience in programming with TensorFlow Micro and deploying TinyML models to an embedded microprocessor and system.
Meet your instructors
- Unfortunately, learners from one or more of the following countries or regions will not be able to register for this program: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this program in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.