Learn practical skills for visualizing, transforming, and modeling data in R. This comprehensive video course shows you how to explore and understand data, as well as how to build linear and non-linear models in the R language and environment. It’s ideal whether you’re a non-programmer with no data science experience, or a data scientist switching to R from other software such as SAS or Excel.
RStudio Master Instructor Garrett Grolemund covers the three skill sets of data science: computer programming (with R), manipulating data sets (including loading, cleaning, and visualizing data), and modeling data with statistical methods. You’ll learn R’s syntax and grammar as well as how to load, save, and transform data, generate beautiful graphs, and fit statistical models to the data.
All of the techniques introduced in this video are motivated by real problems that involved real datasets. You’ll get plenty of hands-on experience with R (and not just hear about it!), and lots of help if you get stuck.
Garrett Grolemund is a statistician, teacher, and R developer who works as a data scientist and Master Instructor at RStudio. He’s conducted corporate training in R at Google, eBay, Axciom, and many other companies, and is currently developing a training curriculum for RStudio. Garrett co-authored the lubridate R package and wrote the ggsubplot package. He received his Ph.D at Rice University.
Table of Contents
Introduction to Data Science with R
- Introduction to the Course 00:15:30
- The R Language 1
- The R Language 2
- Visualizing Data
- Adjusting Graphs
- Tidy Data
- Transforming Data
- Modeling Basics
- Advanced Modeling
- Resources for R 00:03:39
- Title: Introduction to Data Science with R
- Release date: November 2014
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491915028