This project-based sequence guides undergraduate engineering students through the professional lifecycle of an AI product, focusing on industrial engineering practices like requirement engineering, data versioning, experiment tracking, and automated testing. Students simulate the role of an ML Ops engineer to ensure reliability, reproducibility, and ethical compliance in AI systems.