Detecting Anomalies with Machine Learning

Engineers are responsible for detecting abnormalities and ensuring reliability in the products they produce. Developments in artificial intelligence (AI) provide new tools for engineers to quicky identify anomalies and anticipate maintenance needs, preventing costly downtime and failures. Acquiring these skills will enable you to remain competitive and enhance the quality and reliability of your systems.

This course introduces ways to incorporate machine learning and anomaly detection techniques into your familiar process. The examples and projects use real world operational data to give you hands-on practice in applying these techniques to your own work.

You will develop models using real-world data and leverage your existing engineering expertise to guide enhancements using common AI techniques. By the end of this course, you will be able to analyze sensor data, identify abnormal patterns, and implement advanced anomaly detection techniques to address issues before they affect production.

Throughout the course, you’ll have free access to MATLAB to complete the exercises. The apps and functions in MATLAB allow you to apply powerful artificial intelligence algorithms without spending time coding them yourself.