This course focuses on improving data quality specifically for machine learning systems, where poor data directly impacts model accuracy, fairness, and reliability. Learners will understand how to detect, measure, and prevent data issues across the ML lifecycle, from data collection and feature engineering to training, deployment, and monitoring.