Data mining is the effort to reach useful conclusions from data by building interpretive and predictive computational models. This course prepares students to do this through hands-on exploration of data preparation, and model development, tuning, and validation. This is done in the context of various algorithms such as gradient-descent, ensemble methods, and linear regression. Coursework includes multiple significant programming projects and a large final project. Prerequisite: CSC 236. Typically offered annually. Not offered pass/fail.
| Distribution Area | Prerequisites | Credits |
|---|---|---|
| CSC 236 | 1 course |