Predictive Maintenance (Pilot)

Type of course:

Digital learning, Path

Language:

Duration:

1 hour

Proficiency:

Intermediate

Target:

Manager, Professionals, Workers

This course equips manufacturing professionals with the skills to accurately estimate costs across production processes. Through real industrial cases, participants will learn to analyze cost drivers, implement data science techniques for cost forecasting, and develop models to enhance commercial decision-making. The course covers key methodologies for tracking operational expenses and maintain efficiency. By the end, managers and engineers will be able to leverage data-driven approaches to improve cost control, enhance resource allocation, and drive profitability.

Learning outcomes

After the conclusion of this course, the learner will be able to apply relevant data science techniques and tools to process and analyze manufacturing data in solving a predictive maintenance problem for the anticipation of equipment failures and reducing downtime;
After the conclusion of this course, the learner will be able to abstract the predictive maintenance problem and formulate it as a set of appropriate data science and machine learning problems;
After the conclusion of this course, the learner will be able to design and implement an end-to-end data science project for predictive maintenance, incorporating appropriate machine learning models.