Applied Tiny Machine Learning (TinyML) for Scale

XSeries Program

Join Harvard Online in this series of online courses to enhance your knowledge in TinyML, start applying the skills you have developed into real-world applications, and build the future possibilities of this transformative technology at scale.

Featuring faculty from:
View All Courses In This Series

What You'll Learn

Tiny Machine Learning (TinyML) 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 TinyML, start applying the skills you have developed into real-world applications, and build the future possibilities of this transformative technology at scale.

In the first course of the program, Applications of TinyML, you will see how tools like voice recognition work in practice on small devices and you learn how common algorithms such as neural networks are implemented.

In Deploying TinyML, you will experience an open source hardware and prototyping platform to build your own tiny device. The program features projects based on an Arduino board (the TinyML Program Kit) and emphasizes hands-on experience with training and deploying machine learning into tiny embedded devices. The TinyML Program Kit has everything you need to unlock your imagination and build applications based on image recognition, audio processing, and gesture detection. Before you know it, you’ll be implementing an entire tiny machine learning application of your own design.

The final course of this series (MLOps for Scaling TinyML) focuses on operational concerns for Machine Learning deployment, such as automating the deployment and maintenance of a (tiny) Machine Learning application at scale. Through real-world examples spanning the complete product life cycle, you will learn how tiny devices, such as Google Homes or smartphones, are deployed and updated once they’re with the end consumer.

For learners just getting started with TinyML, we recommend beginning with Fundamentals of TinyML.

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. Taught by Harvard Professor Vijay Janapa Reddi along with Lead AI Advocate at Google, Laurence Moroney, Technical Lead of Google’s TensorFlow and Micro team, Pete Warden, and Head of Data/AI Practice, Larissa Suzuki, this program offers you the unique opportunity to learn from leaders and subject matter experts in the AI, Data and ML space and how to apply the emerging world of TinyML at scale.

After completing the XSeries Program in PredictionX, learners will learn:

  • How to gather data effectively for training machine learning models.
  • How to use Python 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.
  • How to automate a MLOps life cycle.
  • Real-world examples and case studies of MLOps Platforms targeting tiny devices.

Series Courses

Read More

MLOps for Scaling TinyML

Experience MLOps through TinyML.

This online course introduces learners to Machine Learning Operations (MLOps) through the lens of TinyML (Tiny Machine Learning).

Read More

Applications of TinyML

Experience TinyML in practice

This online course helps you learn first-hand how to train models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.

Read More

Deploying TinyML

Implement a TinyML application

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.

Enrolling Now

$807 $897USD

3 courses in 2 months

Start Today

Related Courses

Read More

Fundamentals of TinyML

Learn the language of TinyML

This online course focuses on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the language of TinyML.

Read More

CS50's Introduction to Artificial Intelligence with Python

The Foundation of Modern Artificial Intelligence

Join Harvard University Professor David J. Malan in this introductory online course on artificial intelligence to learn how to use machine learning in Python.

Read More

CS50: Introduction to Computer Science

This is CS50x

An introduction to the intellectual enterprises of computer science and the art of programming.