DATA SCIENCE PRACTICUM
Provides an understanding of and experience with turning statistics concepts into practice through data science practicums inspired by realistic projects. Combine theory and methods expertise with communications skills to translate from a vaguely stated project description and complex data set into a concisely summarized analysis, including both written and graphical interpretation that can be used by decision makers in an organization.
Prerequisites & course information
Requisites: Declared in Statistics: Statistics and Data Science MS Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Frame real-world data problems into testable and solvable statistical problems. Audience: Graduate 2. Develop analysis/solutions that are fast, scalable, and robust Audience: Graduate 3. Communicate solutions concisely and clearly, creating understandable and accurate visual/tabular summaries of the data analysis, and responding to audience questions clearly Audience: Graduate Learning Outcomes: 1. Frame real-world data problems into testable and solvable statistical problems. Audience: Graduate 2. Develop analysis/solutions that are fast, scalable, and robust Audience: Graduate 3. Communicate solutions concisely and clearly, creating understandable and accurate visual/tabular summaries of the data analysis, and responding to audience questions clearly Audience: Graduate
Sources
- Course catalogue ↗2026-2027