DATA 201 Classification Analytics
Accessible introduction to data scientific classification. Topics include cross-validation, data partitioning, model building and evaluation, and making predictions. Basic introduction to classification algorithms, and decision trees. Deeper familiarity with a popular data science software platform.
Credits
3
Prerequisite
DATA 101 and
STAT 201 (C- or better), or permission of department chair.