What you'll learn

Organizations collect large amounts of data, but unusual patterns such as fraud, system failures, or unexpected behavior can be difficult to detect using simple rules or manual analysis.

In this course, Traditional Anomaly Detection Methods, you’ll gain the ability to identify unusual patterns in data using foundational anomaly detection techniques.

First, you’ll explore statistical approaches that detect deviations from expected distributions.

Next, you’ll discover distance and density-based methods that identify observations that differ from their neighbors.

Finally, you’ll learn how boundary and isolation-based techniques detect anomalies by modeling normal behavior and separating unusual observations.

When you’re finished with this course, you’ll have the skills and knowledge of traditional anomaly detection needed to investigate and interpret unusual patterns in real-world datasets.