To equip students with the advanced skills needed to design, build, and scale intelligent data systems for industrial and environmental engineering applications, integrating modern data science, scalable computing platforms, and domain-specific methodologies.

Learning Outcomes

By the end of this course, students will be able to:

1. Architect scalable data pipelines for engineering applications
2. Process and analyze large-scale spatiotemporal and sensor datasets
3. Implement machine learning models suited to operational environments
4. Deploy real-time inference and decision-making systems
5. Apply MLOps principles for sustainable model lifecycle management
6. Integrate cloud-based tools and infrastructure into data workflows
7. Design and deliver full-stack capstone solutions for real-world problems