AIS301 Data Pipelines and ETL/ELT Operations

College of Technology Applied AI Department

Course Description: This course explores the design, implementation, and operation of the data pipelines that power modern analytics and AI systems. Students will build and manage workflows using ETL and ELT patterns, and apply core practices in scheduling, dependency management, error handling, logging, and documentation. Emphasis is placed on constructing pipelines that are reliable, repeatable, and auditable — the standards expected in professional data engineering environments. By the end of the course, students will be able to design a functioning data pipeline, diagnose and resolve failures, and document workflows for maintainability and compliance, preparing them to support data-driven decision-making across analytics and machine learning applications.

Credit Hours: 3.00

Prerequisites: All of: CYB310

Corequisites: None