Duration: 4 Weeks 
Prerequisites: Statistics, Linear Algebra, Numerical Methods, and basic AI/ML knowledge

In recent years, the convergence of data science, scalable computing, and engineering domain knowledge has opened new possibilities in solving complex problems in industrial and environmental systems. From optimizing water treatment facilities to predictive maintenance in manufacturing, the ability to process and learn from massive, real-time datasets is a competitive necessity. This course addresses the skills and architectures required to design, deploy, and manage large-scale, intelligent engineering systems in practice.

The course aims to develop the capacity of students to design and implement scalable, intelligent data systems for industrial and environmental applications by integrating advanced data management, analytics, machine learning, and cloud-based computing platforms.