R Programming: Setup and Data Processing

Overview

This course will be useful to anyone who wants to learn the R programming language, particularly to leverage it for data analysis and data science tasks. You will begin by setting up an R development environment and executing simple code. Then, you'll process atomic data types like characters, numbers, and logical. You'll also process data structures like vectors, factors, and data frames. This is the first course in a multi-course Specialization. All of the courses in this Specialization require that you have R and R Studio installed on a Windows PC. The course setup instructions provided in the first module of this course go into more detail about the hardware and software requirements.

Syllabus

Setting Up R and Executing Simple Code

Before you can start developing data science projects in R, you must set up a system with the necessary tools. Then you can create a new programming project and start writing and testing your code.

Processing Atomic Data Types

Now that you have some experience with writing code in R, you can take a deeper dive into the characteristics of the language itself. Like all languages, R categorizes data in different ways. You'll need to know how to process each data type in order to successfully work with your data.

Processing Data Structures

In the previous lesson, you worked with R's atomic data types. These atomic types are components of larger objects that structure data in more complex, yet practical forms. In this lesson, you'll learn how to process the main data structures that R supports.