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edX

Predicting Failures with Machine Learning

MathWorks via edX

Overview

Engineers are tasked with minimizing downtime and enhancing operational reliability. Predictive maintenance has become a powerful way to predict equipment failures before they occur, leading to increased efficiency and cost savings. With operational efficiency being crucial to competitiveness, companies are seeking engineers with skills in applying predictive maintenance techniques. This course provides engineers with artificial intelligence (AI) skills to proactively identify potential equipment failures, thereby boosting efficiency and reducing operational costs.

In this course, you will learn to seamlessly integrate machine learning into maintenance strategies, anticipating potential issues and improving operations. You'll engage with real-world engineering scenarios, gaining hands-on experience in analyzing sensor data and developing predictive models. By the end of the course, you'll be able to design and implement AI-driven maintenance solutions, leveraging your engineering expertise to guide AI applications.

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.

Taught by

Kathy Tao, Rohit Ramanathan, Marissa D'Alonzo, Brian Buechel and Megan Thompson

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