Anomaly Detection is a data analysis process that identifies data points, events, or observations that deviate from the established norm or behavior. Coursera's Anomaly Detection catalogue schools you on the advanced techniques used to detect abnormal patterns or anomalies in data. You'll learn about different types of anomalies and the statistical techniques used to distinguish them, how to build predictive models for anomaly detection, and how to apply these models in various fields such as cybersecurity, finance, health, and many more. This skill will also equip you with the ability to use machine learning and AI for detecting anomalies, enhancing your capabilities as a data scientist, software engineer or any professional dealing with big data.