Detecting Anomalies with Machine Learning

Overview

Engineers play a pivotal role in detecting abnormalities and ensuring the reliability of the products they create. Recent advancements in artificial intelligence (AI) offer innovative tools for engineers to swiftly identify anomalies and predict maintenance needs, helping to avoid costly downtime and failures.

By acquiring these skills, you can maintain a competitive edge and improve the quality and reliability of your systems.

This course explores how to integrate machine learning and anomaly detection techniques into your existing processes. You'll engage with real-world operational data through examples and projects, gaining hands-on experience in applying these techniques to your work.

Participants will develop models using actual data, utilizing their engineering knowledge to guide improvements through common AI techniques.

By the course’s conclusion, you will be adept at analyzing sensor data, spotting irregular patterns, and implementing cutting-edge anomaly detection methods to preemptively tackle issues that could disrupt production.

Throughout the duration of the course, you will have complimentary access to MATLAB, which will be essential for completing the exercises. With MATLAB's apps and functions, you can apply robust AI algorithms without the need for extensive coding.

Offered by edX, this course falls under categories such as Artificial Intelligence, Machine Learning, Anomaly Detection, Data Science, Time Series Analysis, MATLAB, Signal Processing, and Pattern Recognition Courses.

Subjects