Anomaly Detection

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.
28credentials
80courses

Most popular

Trending now

New releases

Filter by

Subject
Required

Language
Required

The language used throughout the course, in both instruction and assessments.

Learning Product
Required

Build job-relevant skills in under 2 hours with hands-on tutorials.
Learn from top instructors with graded assignments, videos, and discussion forums.
Learn a new tool or skill in an interactive, hands-on environment.
Get in-depth knowledge of a subject by completing a series of courses and projects.
Earn career credentials from industry leaders that demonstrate your expertise.
Earn career credentials while taking courses that count towards your Master’s degree.

Level
Required

Duration
Required

Subtitles
Required

Educator
Required

Explore the Anomaly Detection Course Catalog

What brings you to Coursera today?

Leading partners

  • Microsoft
  • Johns Hopkins University
  • University of Colorado Boulder
  • EDUCBA
  • Google Cloud
  • MathWorks
  • Packt
  • IBM