R is an open source software environment for statistical computing and graphics and is very popular with data scientists. R is being used for data analysis, extracting and transforming data, fitting models, drawing inferences, making predictions, plotting, and reporting results. Learn how to use R basics, working with data frames, data reshaping, basic statistics, graphing, linear models, nonlinear models, clustering, and model diagnostics.
You Will Learn
- How to configure the RStudio environment and load R packages
- How to use R basics such as basic math, data types, vectors, and calling functions
- How to use advanced data structures such as data frames, lists, and matrices
- How to use R base graphics
- How to use R basic statistics, correlation, and covariance
- How to use linear models such as simple linear regression, logistic regression
- How to use nonlinear models such as decision trees and random forests
- How to apply clustering using k-means
- How to complete model diagnostics
- Anyone interested in learning to use data mining techniques to find insights in data and who has at least some statistical and programming experience.