Course Working with the RStudio IDE (Part 1)

Learn the basics of the important features of the RStudio IDE.


This online course about Working with the RStudio IDE (Part 1) covers a key part of what a future data analyst would require.

Enroll now in this Working with the RStudio IDE (Part 1) course, and don’t miss the opportunity of learning with the best, as Garrett Grolemund is. With 69 enriching exercises, 24 videos, and an estimated time of 3 hours to successfully end up the course, you will become one of the best.

Requisites before you start
Chapter 1: Orientation
This chapter shows you around the most important parts of the RStudio IDE. You’ll learn about the data viewer, the environment tab, the history tab, how to set and get your working directory, using the plots pane, navigating the help tab when you get stuck, and more.
Chapter 2: Programming
This chapter builds on the last by showing you how to take advantage of the IDE for a more efficient and enjoyable R programming experience. For example, you’ll see how RStudio’s built-in code and style diagnostics can flag things before they go terribly wrong. You’ll learn tricks for using multiple cursors at once, collapsing code for better visibility, and using RStudio’s handy tools for debugging your code.
Chapter 3: Projects
In this brief chapter, you’ll see how to use RStudio projects to organize and share your code with others. Projects come with many benefits, including the ability to keep all relevant files in one place and to easily search all of these files with a single command. You’ll also be exposed to the Packrat system for package management and reproducibility.
Chapter 4:
Working with the RStudio IDE (Part 1). Learn the basics of the important features of the RStudio IDE.

Garrett Grolemund

Data Scientist at RStudio

Garrett is the author of Hands-On Programming with R and R for Data Science from O’Reilly Media. He is a Data Scientist at RStudio and holds a Ph.D. in Statistics, but specializes in teaching. He’s taught people how to use R at over 50 government agencies, small businesses, and multi-billion dollar global companies; and he’s designed RStudio’s training materials for R, Shiny, dplyr and more and is a frequent contributor to the RStudio blog. He wrote the popular lubridate package for R.


#R #Python #MachineLearning #BigData #DataAnalysis