Tiny Machine Learning (TinyML) is a cutting-edge field that brings the transformative power of machine learning (ML) …
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.
What you 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.
