An introductory course to spatial artificial intelligence (AI), providing a big picture of spatial AI applications (e.g., Google Maps, Uber/Lyft, Earth observation, smart cities, autonomous vehicles), techniques, platforms, trends, debates, etc. The course will cover basics of AI, identify challenges faced by AI techniques in the context of spatial data and applications, and introduce spatial-aware AI methods to address them. AI topics include but are not limited to: spatial data models and representation, machine learning, deep learning, navigation/planning, trends including large language models and foundation models for geospatial data, etc. Students are expected to have a broad understanding of spatial AI concepts, develop intuitions and insights to AI techniques, and have hands-on experience with Python at the end of the course.