AI and ML for Industry 4.0

AI & Machine Learning for Industry 4.0 introduces participants to the application of artificial intelligence and machine learning technologies in modern industrial environments. The course covers how AI and ML can support smart manufacturing, automation, predictive maintenance, quality control, and process optimization. Participants learn the fundamentals of machine learning, including supervised, unsupervised, and basic deep learning concepts. The course explains how industrial data from sensors, machines, PLCs, SCADA, and IoT systems can be collected and prepared for AI applications. Participants explore data preprocessing, feature engineering, model development, training, testing, and performance evaluation. Practical applications such as predictive maintenance, anomaly detection, demand forecasting, and automated quality inspection are discussed. The course also introduces Python-based tools and libraries commonly used for industrial AI and machine learning. Participants gain an understanding of how AI models can be integrated with Industry 4.0 systems and smart factory architectures. Real-world industrial examples and demonstrations help connect theoretical concepts with practical engineering applications. By completing the course, participants develop a foundation for identifying and implementing AI and ML solutions for industrial operations.