Transfers ToNot transferableDescriptionIntroduction to the design and implementation of scalable data infrastructure. Topics include data ingestion techniques, storage architectures, horizontal and vertical scaling strategies, ETL pipeline development, and model deployment (MLOps). Explores workflow orchestration, data modeling for analytics, and containerization. Students gain practical experience building automated data workflows using Python, SQL, and open-source tools, with less emphasis on complex distributed systems theory.