An applied introduction to the fast-evolving field of artificial intelligence with a focus on using supervised learning models (such as image classifiers) and foundational models (such as large language models) in various interdisciplinary domains. Designed for students without a programming background, this course is accessible to a broad audience and emphasizes critical analysis of the role of data, the limitations and failure modes of AI systems, and the societal impact of AI systems, including risks, ethics, and safety.