KAUST Academy, in cooperation with UNESCO Abdus Salam International Centre for Theoretical Physics (ICTP) and KAUST UNESCO Chair on Education to Connect the UnConnected, announce the hosting of the Tiny Machine Learning (TinyML) course. This course is scheduled to take place at KAUST from January 4 to 11, 2024.
The program aims to focus on integrating machine learning functions into low-power embedded systems. It also seeks to bridge the gap between machine learning and the increasingly prevalent infrastructure of the internet-of-things. By expanding the capabilities of artificial intelligence to include a wide range of devices, this course will enable the making of smart and instant decisions in various applications, such as medical and industrial ones, enhancing their connectivity and adaptability to user needs.
The course will provide an overview of the fundamental concepts and principles underlying TinyML systems. It will introduce various sensing technologies used in these systems, as well as methods for data collection, filtering and preprocessing.
Additionally, the course will offer a practical demonstration of prevalent Internet of Things platforms and protocols, illustrating their ability to establish connections between sensors, actuators and other internet-connected devices.
Finally, the course will explore ethical considerations and privacy issues associated with the internet, fostering a comprehensive understanding of these critical aspects in the context of TinyML systems.
