AI Applied to Health and Injury Prevention

About this course

This specialization explores how artificial intelligence and modern data science are transforming athlete health, injury prevention, and long-term performance management. Learners will build a deep and practical understanding of how AI enhances the prevention, monitoring, and prediction of injuries, from foundational models of injury causation to advanced approaches using machine learning, biomarkers, hormonal data, and multi-modal monitoring systems. Learners will examine how etiological frameworks, workload models, contextual factors, biological rhythms, and maturation processes shape injury risk throughout an athlete’s life cycle. Through football-specific examples, the specialization explains how AI systems integrate data from GPS sensors, wearables, sleep tracking, subjective wellness monitoring, menstrual-cycle information, and environmental conditions to create individualized risk profiles and early-warning systems. The program also explores the growing role of precision medicine, AR/VR rehabilitation, mental-health monitoring, and smart-stadium technologies in protecting athlete wellbeing. Ethical and governance considerations, such as data privacy, bias, autonomy, and fairness, are woven throughout to prepare learners for responsible use of AI in professional sport. By completing this specialization, learners will be able to apply AI-enhanced strategies to reduce injury burden, personalize training, and support healthier, more sustainable athletic careers.

Course objectives

• Foster a practical understanding of AI in injury prevention
• Equip learners with skills for personalizing training strategies
• Prepare learners to responsibly use AI systems in professional sports