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Achieving the full capability of AI requires a system perspective, extending beyond the models, to effectively leverage algorithms, data, and computing power. Creating AI-enabled systems includes thoughtful consideration of an operational decomposition for AI solutions, engineering data for algorithm development, and deployment strategies. The objective of this course is to bring a system perspective to creating AI-enabled systems. The course will explore the full-lifecycle of creating AI-enabled systems starting with problem decomposition and addressing data, development, design, diagnostic, and deployment phases. Each module will either introduce a domain in Machine Learning (Tabular, Computer Vision, Natural Language Processing, and Physical Systems) or delve into the end-to-end development of a specific AI system. Students will be exposed to the common technologies and resources practitioners use to develop these systems.