The University of Cambridge’s Professional and Continuing Education (PACE), in collaboration with Arm Education, has developed an online course, AI at the Edge on Arm, now available on edX.
The course provides a practical introduction to deploying artificial intelligence on edge devices, bringing machine learning capabilities directly to low-power systems such as microcontrollers and embedded platforms. Learners gain an understanding of how AI can operate closer to the source of data, where performance, efficiency, and real-world impact come together.
Bringing together academic insight and industry expertise, the course offers a hands-on, skills-focused learning experience designed to help learners build knowledge in an area of growing importance across the digital and technology sectors.
Professor Ali Al-Sherbaz, Academic Director for Digital Skills at PACE, leads the Cambridge contribution. With more than 25 years of experience in academia and research, his work spans cybersecurity, networks, and artificial intelligence. He has led numerous national and international projects and is a Fellow of the Higher Education Academy, BCS, and IET.
He is joined by Dr Michele Magno, Head of the Centre for Project-Based Learning at ETH Zürich’s Department of Information Technology and Electrical Engineering. His research focuses on Tiny Machine Learning, smart sensing, and energy-efficient IoT systems. A senior IEEE member and author of more than 200 scientific papers, Dr Magno brings extensive experience in low-power embedded intelligence.
Reflecting on the collaboration, Professor Al-Sherbaz said:
"The partnership between PACE and Arm represents an exciting step forward in bridging academic insight with industry innovation. The AI at the Edge on Arm course empowers learners to understand how intelligent systems operate close to the source of data, where performance, efficiency, and real-world impact converge. It’s a perfect example of how Cambridge continues to connect cutting-edge research with practical applications in the digital economy."
Designed for students, professionals and enthusiasts with a background in computer science, electronics or engineering, AI at the Edge on Arm offers an application-focused introduction to edge AI in practice.