INE599Z Machine Learning for Industrial & Mechanical Engineering

[3–0, 3 cr.]

The course provides a high-level introduction to Machine Learning (ML) tailored for industrial and mechanical engineering students. It focuses on conceptual understanding of how ML methods learn from data to support prediction, classification, pattern recognition, and decision-making in engineering systems. Through visual explanations, case studies, and guided demonstrations using pre-built notebooks, students explore key ML approaches, including supervised and unsupervised learning, model evaluation, and basic reinforcement learning, and learn how these methods are  applied in real mechanical and industrial engineering contexts. The students will participate in guided computer-lab sessions to run and interpret ML models using pre-structured tools.

Prerequisites: GNE333 Probability and statistics, COE 212, INE212 or MEE212, 4^th year standing.