A Hands-on University Short Course for Edge AI

This paper aims to present a hands-on short course for Edge AI to university students of Computer Science and Engineering departments. Edge Computing is a modern, distributed computing architecture that brings data storage and computation closer to the source of data generation instead of being sent to the Cloud. This approach provides several benefits to a modern IoT network such as bandwidth savings and improved response time. We propose an Edge Computing short course that includes theoretical knowledge reinforced with hands-on laboratory exercises. Our course syllabus combines different cutting edge technologies like Embedded systems, Artificial Intelligence and Machine Learning. For the implementation of the Edge Computing laboratory exercises we selected the Raspberry Pi Single Board Computer (SBC) to inference ML workloads applying different configurations. The proposed short course provides students the opportunity to develop expertise in Edge Computing and enforce skill development to manage projects that may encounter in a professional carrier.