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Individual Course

Applications of TinyML

Course Length

6 weeks

2-4 hours per week

Featuring faculty from:

Harvard John A. Paulson School of Engineering and Applied Sciences LogoHarvard John A. Paulson School of Engineering and Applied Sciences

Enroll as Individual

Certificate Price:

$ 299

Enroll as Individual

Certificate Price:

$ 299

Learn first-hand how to train models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.

Do you know what happens when you say “OK Google” to a Google device? Is your Google Home always listening? Following on the Foundations of Tiny ML course, Applications of TinyML will give you the opportunity to see tiny machine learning applications in practice. This course features real-world case studies, guided by industry leaders, that examine deployment challenges on tiny or deeply embedded devices. Dive into the code for using sensor data for tasks such as gesture detection and voice recognition. Focusing on the neural network of the applications, specifically on training and inference, you will review the code behind “OK Google,” “Alexa,” and smartphone features on Android and Apple . Learn about real-word industry applications of TinyML as well as Keyword Spotting, Visual Wake Words, Anomaly Detection, Dataset Engineering, and Responsible Artificial Intelligence. Tiny Machine Learning (TinyML) is one of the fastest-growing areas of deep learning and is rapidly becoming more accessible. The second course in the TinyML Professional Certificate program, Applications of TinyML shows you the code behind some of the world’s most widely-used TinyML devices. The course will be delivered via edX and connect learners around the world.

Self-Guided

edX

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Faculty

Your Instructor

Laurence Moroney

Lead AI Advocate at Google

Laurence Moroney leads AI Advocacy at Google, working as part of the Google Research into Machine Intelligence (RMI) team. He's the author of more programming books than he can count, including 'AI and Machine Learning for Coders' with OReilly, published in October 2020.

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Your Instructor

Vijay Janapa Reddi

Associate Professor at John A. Paulson, School of Engineering and Applied Sciences (SEAS) at Harvard University

Vijay Janapa Reddi is an Associate Professor at Harvard University, Inference Co-chair for MLPerf, and a founding member of MLCommons, a nonprofit ML (Machine Learning) organization aiming to accelerate ML innovation.

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An example HarvardX certificate

Ways to take this course

Audit or Pursue a Verified Certificate

A Verified Certificate costs $299 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate.

⁠Alternatively, learners can Audit the course for free and have access to select course material, activities, tests, and forums. Please note that this track does not offer a certificate for learners who earn a passing grade.

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