DATA 202 Estimation and Clustering Analytics
Accessible introduction to data scientific estimation and clustering. Topics include estimation algorithms such as linear regression and clustering algorithms such as k-means clustering, and making predictions. Topics may include multiple regression modeling, model building, hierarchical clustering, and evaluating cluster goodness. Deeper familiarity with an open-source data science platform, such as R.