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This course seamlessly integrates health science and artificial intelligence (AI), offering a dynamic approach to propel both domains forward. Embracing project-based learning, the curriculum ensures students acquire both theoretical knowledge and hands-on experience in cutting-edge AI applications within health science research and management. Topics covered include (1) foundational AI concepts such as machine learning and deep learning, (2) computer vision models, (3) language models, (4) graph models, (5) AI for multi-omics data analysis, (6) drug discovery, and (7) disease diagnosis and prognosis. The emphasis is on cultivating an understanding of AI technologies, enabling biomedical students to apply AI tools effectively to address health science inquiries through curated datasets and practical exercises. This interdisciplinary course is designed to bridge the gap between health science and AI, empowering biomedical students with learned AI skills to contribute meaningfully to advancements in health science research and management.