This course will enable students to have an in-depth understanding of embedded AI algorithms and their implementation in real systems and applications. The major topics include 1) basics on machine learning; 2) data and system challenges in embedded AI 3) AI techniques and their implementation on cutting-edge platforms 4) real-world applications, such as smart health and smart buildings. The course structure will primarily consist of instructor presentations, student presentations, paper summaries, and a course project. Students will work on an individual or team project to build an end-to-end system. Students will also read and discuss the latest publications in the areas of embedded AI, Internet of Things, mobile systems, and ubiquitous computing.