R Programming in Data Science: Setup and Start

Description

In this course, you will :

• Provides a quick and easy introduction to the many flavours of the R programming language, such as base R, tidyverse R, R Open from Microsoft, and Bioconductor R.
• Also includes a look at programming with R interactively and from the command line, as well as some useful packages for working with SQL, 3D graphics, data, and clusters in R.
• You will have installed a version of R, as well as a few core libraries and an optimised IDE, by the end of this short course.

Syllabus :

1. Set Up Base R

• Why is base R unique?
• Check to see if R is installed
• How to install base R
• Development environments for base R
• A comparison task in base R
• An optimal task for base R

 

2. Set Up tidyverse R

• Why is the tidyverse unique?
• How to install the tidyverse
• A comparison task using the tidyverse
• An optimal task for the tidyverse

 

3. Set Up Microsoft R Open

• Why is Microsoft R Open unique?
• How to install Microsoft R Open
• Development environments for Microsoft R Open
• A comparison task using Microsoft R Open
• An optimal task for Microsoft R Open

 

4. Set Up Bioconductor R

• Why is Bioconductor R unique?
• How to install Bioconductor R
• Development environments for Bioconductor R
• A comparison task using Bioconductor R
• An optimal task for Bioconductor R

 

5. First Look at R Programming

• Use R interactively
• Use R with command-line arguments

 

6. Most Common R Packages

• sqldf
• rgl
• data.table
• cluster

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