BIT-3484: Advanced Business Analytics in Python and R

Description: Python and R for advanced data analysis, including predictive analytics and machine learning, to support business decisions. Use Python and R to conduct exploratory data analysis. Learn how to handle data, sampling distributions, statistical experiments, and significance testing in Python and R. Apply simple and multiple linear regression and related concepts such as confidence intervals, dummy variables, correlation, multicollinearity, confounding variables, interactions and main effects, and outliers. Learn how to apply classification, specifically NaΪve Bayes, discriminant analysis, and logistic regression. Learn how to apply model evaluation techniques such as ROC curves, AUC, and lift. Introduction to and application of machine learning, including k-nearest neighbors, tree models, principal component analysis, and hierarchical clustering.

Pathways: N/A

Course Hours: 3 credits

Corequisites: N/A

Crosslist: N/A

Repeatability: N/A