Harvard

Vijay Janapa Reddi

Pete Warden

In this course, you will learn how to program and deploy TinyML models to microcontroller-based devices. The course covers the hardware and software aspects of microcontrollers, providing you with the skills to implement applications such as voice recognition, sound detection, and gesture detection. With a focus on practical projects, you'll gain experience with the TinyML Program Kit, which includes an Arduino board and an ARM Cortex-M4 microcontroller.

Deploying TinyML

Gain insights into the hardware components of microcontroller-based devices and their functionalities.

Understanding Microcontroller Hardware

Explore the software aspects of microcontrollers, including programming and deployment techniques.

Software for Microcontrollers

Learn how to write code and deploy machine learning models to microcontroller-based devices.

Programming TinyML Devices

Understand the process of training microcontroller devices for various applications.

Training Microcontroller Devices

Explore the ethical considerations and best practices for deploying AI models responsibly.

Responsible AI Deployment

Deploying TinyML is a unique course that combines computer science and electrical engineering to teach you how to build and deploy TinyML applications. Gain hands-on experience with embedded systems and machine learning deployment using TensorFlow Lite for Microcontrollers.

Individuals looking to gain hands-on experience with embedded systems and microcontroller-based devices.

Aspiring Embedded Systems Engineers

Learners interested in applying machine learning models to physical devices and exploring TinyML applications.

Machine Learning Enthusiasts

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Deploying TinyML

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