Manufacturing systems generate massive amounts of data, yet issues are often discovered only after they impact performance. As a result, engineers are increasingly expected to work with data to identify problems earlier and improve outcomes. In this Professional Certificate from MathWorks, you'll build practical machine learning skills for manufacturing and industrial systems to detect anomalies, analyze system behavior, and improve operations.
Designed for manufacturing engineers, systems engineers, process engineers, and technical professionals, this program focuses on applying machine learning in environments where large volumes of sensor, process, and operational data are difficult to interpret in time to prevent issues. Through a structured sequence of courses, you'll do hands-on work with industry-relevant data and engineering workflows to analyze system behavior, identify abnormal conditions, and evaluate performance. The program progresses from core concepts to practical applications such as quality monitoring, fault detection, predictive monitoring, and process optimization, reflecting real engineering practice.
By the end of the program, you'll be able to analyze manufacturing data, identify issues early, and make data-driven decisions. These skills are increasingly important as organizations adopt analytics and industrial machine learning to improve efficiency and reliability. They also enable progression into roles such as manufacturing engineers, systems engineers, and industrial engineers across industries including automotive, aerospace, energy, electronics, and industrial equipment.
Created by MathWorks, the developer of MATLAB, this Professional Certificate emphasizes tools and workflows widely used in engineering practice. You'll use MATLAB throughout the courses to build skills that transfer directly to your day-to-day work. As a platform widely used by engineers and scientists in manufacturing and R&D, MATLAB enables you to apply these skills across companies and roles as you advance your career.
