3 credits
Spring 2026 Lecture Distance Learning Upper Division
Students follow a structured analytical process using popular industry tools (e.g., RStudio, Tableau, SQL) to identify, visualize, and summarize relationships within large data sets to support business problems. More focus is on descriptive analytics which includes business segmentation and clustering methods, but also introduces two predictive analytic methods, decision trees, and neural networks.
Learning Outcomes1Demonstrate working knowledge of relationship databases, SQL queries, and efficient sampling.
2Demonstrate working knowledge of RStudio to perform EDA, visualization, and data mining techniques.
3Demonstrate working knowledge of data visualization and exploration using Tableau.
4Demonstrate practical understanding of popular unsupervised and supervised learning methods.
Prerequisites
Restrictions
made by Purdue students.