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The Harvard John A. Paulson School of Engineering and Applied Sciences tinyML Foundation google Edge Impulse International Centre for Theoretical Physics (ICTP) Arduino edX HarvardX TensorFlow Lite for Microcontrollers

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Foundations of TinyML

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.

Take the Course on edX

Applications 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.

Take the Course on edX

Deploying TinyML

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.

Take the Course on edX

MLOps for Scaling TinyML

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.

Take the Course on edX

Introduction to Embedded Machine Learning

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.

Take the Course on Coursera

Computer Vision with Embedded Machine Learning

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.

Take the Course on Coursera


Build and Teach Your Own Course


You can find lots of educational materials on TinyML below. They are all free and open-source for educational uses – we just ask that if you use the materials that you cite them!

We are also trying to track and provide links to others to all TinyML course materials that are created to make it even easier for others to launch courses so we ask that if you create a course based on these materials that you consider posting your materials publicly and sending us a link so we can add it to the table below.

Finally, if you want to be more involved with our effort to help improve access to TinyML educational materials and hardware resources worldwide please check out the TinyML4D working group!

Questions, comments, concerns, suggestions for improvement – reach out to us at edu@tinyML.org!

Full Courses

  Course Name Date of Course Target Audience Language of Instruction Language of Materials Links
Harvard John A. Paulson School of Engineering and Applied SciencesedX edX tinyML Specialization
by Harvard University
Launched 2020-2022 Everyone English English Course 1-3 Website
Course 4 Website
All Materials
All Colabs
Arduino Library
Edge ImpulseCoursera Embedded Machine Learning on Coursera
by Edge Impulse
Launched 2021-2022 Everyone English English Course 1
Course 2
All Materials
Universidade Federal de Itajubá (UNIFEI) UNIFEI IESTI01
TinyML - Machine Learning for Embedding Devices
Jan 2021 - Present Undergraduate Students Portuguese English 2022.1 Website and Materials
2021.2 Website and Materials
2021.1 Website and Materials
Harvard John A. Paulson School of Engineering and Applied Sciences Harvard CS249r
Tiny Machine Learning
Sept-Dec 2020 Graduate Students English English Website
Assignments

Workshops

Lead Organizers Workshop Name Date of Workshop Target Audience Language of Instruction Language of Materials Links
Harvard John A. Paulson School of Engineering and Applied SciencesThe Abdus Salam International Centre for Theoretical Physics (ICTP)TinyML Foundation SciTinyML 2022
Africa, Asia, and Latam

Scientific Use of Machine Learning on Low-Power Devices
April, June, July 2022 Everyone English / Spanish for Latam English / Spanish for Latam Website and Materials
Harvard John A. Paulson School of Engineering and Applied SciencesNavajo Technical UniversityBarnard CollegeIEEE Computer Society EASI-22
2022 Edge AI Summer Institute
June 2022 High School Students and Teachers English English Website and Materials
Harvard John A. Paulson School of Engineering and Applied SciencesThe Abdus Salam International Centre for Theoretical Physics (ICTP)TinyML Foundation SciTinyML 2021
Scientific Use of Machine Learning on Low-Power Devices
October 2021 Everyone English English Website
Materials
Harvard John A. Paulson School of Engineering and Applied SciencesGoogleNavajo Technical UniversityEdge ImpulseTFLite Micro CRESTLEX 3.0
CReating Effective STem Learning EXperiences
June 2021 Middle and High School Students and Teachers English English Website and Materials

Books

  Title Author(s) Date of Publication Target Audience Language Links
TinyML TinyML
Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
Pete Warden
Daniel Situnayake
January 2020 Everyone English Website
TinyML Cookbook TinyML Cookbook
Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter
Gian Marco Iodice
April 2022 Everyone English Website

For more materials (Seminars / Tutorials / Demos / etc.) check out the TinyML4D Past Events Page.

We’ve included some of our favorites below!

  Title Author(s) Date Target Audience Language of Instruction Language of Materials Links
Universidade Federal de Itajubá (UNIFEI) Getting Started with the Arduino TinyML Kit Marcelo Rovai
March 11, 2022 Everyone English English Video
Slides
Handout
Harvard John A. Paulson School of Engineering and Applied Sciences Why the Future of ML is Tiny and Bright Vijay Janapa Reddi
September 17, 2021 Everyone English English Video
Slides

Explore our Working Groups

Widening access to applied machine learning by establishing best practices in education.


If you want to be more involved with our effort to help improve access to TinyML educational materials and hardware resources worldwide reach out to us at edu@tinyML.org!

TinyML4D

TinyML4D

The TinyML4D working group is building a network of academic institutions, based in Developing Countries, interested in expanding access to Applied Machine Learning by establishing best practices in education. We aim to ultimately develop a community of researchers and practitioners focused on both improving access to TinyML education and enabling innovative solutions for the unique challenges faced by Developing Countries. TinyML4D is co-hosted by the Abdus Salam International Centre for Theoretical Physics (ICTP).

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TinyML4K12

TinyML4K12

Expanding TinyML education into primary and secondary schools (K-12) requires the development of an end-to-end pipeline that is appropriate for school-aged children. We are working with education and industry partners to combine computer science education software and the physical computing ecosystem to enable an easy learning experience for creating, deploying, and using TinyML models. This pipeline will enable the creation of additional materials that can be used across the globe for students of all ages.

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TinyML4Xlation

TinyML4Xlation

Our mission is to enable all learners, regardless of their preferred language of learning, to be able to access and learn TinyML. As such, we work to translate and support material and course development in languages other than English.

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TinyML4STEM

TinyML4STEM

TinyML can be a great way to explore STEM concepts. We are working to integrate TinyML into other STEM disciplines to develop exciting hands-on curricula. We invite you to help join the community effort to develop, improve, and expand upon these materials. Together we can build new exciting projects to foster STEM education.

Learn More