AI-DRIVEN PROGNOSTICS FOR INDUSTRIAL SYSTEMS

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  • DURATION
    2 WEEKS
  • SUBJECT AREA
    Production and Logistics
  • COURSE LEVEL
    Second Cycle
  • CREDITS
    0.0 HP
  • INSTITUTION
    REEDEAM
  • STUDY TYPE
    Distance
  • END DATE
    2025-01-15

COURSE DESCRIPTION

This course has flexibel start and you may join between October 21 and November 17, 2024

This course is designed for engineers, scientists, operators, and managers interested in utilizing AI-based methods for condition monitoring and prognostics in industrial systems and high-value assets. Participants will learn to identify common failure causes and predict Remaining Useful Life (RUL) using historical data, involving tasks such as data processing, feature selection, model development, and uncertainty quantification. Led by experienced professionals from industry and academia, the course covers the basics of prognostics and introduces various AI methods, including deep learning. It represents state-of-the-art AI-driven prognostic techniques, advanced signal processing, and feature engineering methods.

You may join the course any time between October 21 and November 17, 2024. With the recommended study pace of 25%, the course would take approximately seven calendar weeks to complete. Higher or lower study pace is possible as long as the course is finished no later than January 15, 2025.

Scheduled online meetings

November 11th 2024

January 15th 2025

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