This course covers data-driven process improvement and automation applications in industrial engineering. Topics include process mapping, data collection and cleaning, exploratory data analysis, feature engineering, classification and regression, clustering, anomaly detection, forecasting, decision support systems, process mining, intelligent scheduling and routing, predictive maintenance, quality control, computer vision, RPA, and the foundations of MLOps. AI Agent and common open-source tools are used in the practical sessions. The course develops small prototypes, uses real industrial cases, and emphasizes ethical use, explainability, and organizational integration.
- Öğretmen: Ümran Kaya