Traditional machine learning tends to be centralized in nature (e.g., in the cloud). However, security and privacy concerns as well as the availability of abundant data and computational resources in wireless networks motivate moving learning algorithms deployed on mobile networks towards the network edge. This has led to the emergence of the rapidly growing area of (mobile) edge learning, which integrates two originally decoupled areas: wireless communication and machine learning. It is widely expected that the advancements in edge learning will provide a platform for implementing edge artificial intelligence (AI) in 5G-and-Beyond systems and supporting large-scale problems ranging from autonomous driving to personalized healthcare. Thus, this proposed full-day workshop will seek to bring together researchers and experts from academia, industry, and governmental agencies to discuss and promote the research and development needed to overcome the major challenges that pertain to this cutting-edge research topic.