BAN485 Data Mining II: R, Python, and Applied AI

College of Business and Criminal Justice Business Department

Course Description: This course develops practical data fluency for future business leaders through a low-code/no-code approach to Python and SQL. Students begin with no-code and visual tools to explore data, build queries, and generate reports, then progress to guided low-code applications using AI assistants, templates, and automation tools. Emphasis is placed on framing effective business questions, validating data sources, cleaning and organizing information, and transforming results into clear, actionable insights. Students examine how emerging technologies, including AI coding assistants, cloud data platforms, and automated reporting tools, support business decision-making while also considering accuracy, governance, ethics, and data privacy. Applied work throughout the course helps students connect data analysis practices to workplace contexts and document their processes in a clear, reproducible way.

Credit Hours: 3.00

Prerequisites: All of: BAN385

Corequisites: None