Driven by recent advancements in artificial intelligence (AI) and mobile edge computing (MEC), edge intelligence has emerged as a promising paradigm to support AI model training and inference over wireless networks. This postgraduate-level course aims to equip students with an understanding of edge intelligence from both communication and computing perspectives. The course begins by laying the groundwork with the fundamentals of wireless communications and mobile networks, followed by an exploration of the concepts and key technologies underpinning MEC. Building on this foundation, federated edge learning will be introduced, including its system modeling, convergence analysis, differential privacy mechanisms, and the integration of communication and learning design. Lastly, the course delves into device-edge co-inference techniques and the applications of edge intelligence in transportation, such as infrastructure-vehicle cooperative autonomous driving.