Data Acquisition and Management

Catalog description

This course provides a comprehensive foundation in acquiring, managing, and preparing data for use in intelligent systems and data-driven applications. Students will explore the full data lifecycle, from sourcing and ingestion to cleaning, transformation, storage, and retrieval within the context of real-world technical and ethical challenges. Topics include web scraping, API integration, database design, data warehousing, ETL pipelines, data governance, and schema evolution. Students will also address data quality assurance, handling unstructured data, version control, and compliance with legal and ethical standards related to privacy and ownership. Special attention is given to managing large-scale, multi-source datasets in AI and machine learning workflows. By the end of the course, students will be able to design robust data infrastructures that supports scalable AI applications.