Detect AI Anomalies: Real-Time Outliers

Detect AI Anomalies: Real-Time Outliers is an intermediate course for MLOps engineers and data scientists tasked with ensuring AI systems are reliable in production. Static alerts fail when data is dynamic, leaving systems vulnerable to silent failures. This course teaches you to build an intelligent early warning system that catches critical issues before they escalate. You will learn to apply statistical methods like Z-score and Exponentially Weighted Moving Average (EWMA) on streaming data to detect sudden outliers with dynamic thresholds. You will then go beyond simple statistics, using u…