The vision of the learning precision health is to leverage technology, data analytics, and evidence-based practices to create a feedback loop that continuously informs and improves healthcare delivery, policy, and practice, with the goals of preventing disease occurrence, detecting diseases earlier, and advancing human health. Rapid advances in computing generally and artificial intelligence (AI) specifically, suggest that data collection, analysis and modelling will be increasingly important to learning precision health. This workshop will provide a comprehensive overview of learning precision health, highlighting the role of real-world evidence in improving patient outcomes and healthcare efficiency. Participants will gain insights into the foundational principles of learning precision health, the technologies that support them, and practical steps for their implementation, especially in the domains of cancer, aging, psychiatry and rare diseases. Through interactive sessions and expert presentations, attendees will learn how to leverage data science, informatics and AI to create a continuous learning environment within their healthcare organizations.