Assess students' ability to design, implement and interpret wearable-sensor–driven machine learning load-management systems to predict and prevent overuse injuries in elite endurance runners; scope includes sensor selection (IMU, GPS, HR, pressure), signal processing and feature engineering, training-load metrics, model choice and validation (time-series methods, classifiers, survival models), handling imbalance and small cohorts, performance metrics and clinical utility, translating model outputs into evidence-based load-adjustment interventions, and considerations for ethics, data quality, and deployment with coaches and support staff.