Introduction to Data Analysis in R
In the world of data science, R is a popular programming language for a reason. It was built with statistical manipulation in mind, and there’s an incredible ecosystem of packages for R that let you do amazing things – particularly in data visualization – that would be much more difficult in Python.
This is the first course in our Data Analyst in R path, and in it you'll be learning about the fundamentals of R. You'll learn to use variables, operators, and write logical expressions. You'll also learn about the data analysis workflow in R.
As you learn these new R programming skills, you'll be writing your own code to practice them right in your browser window. And you’ll learn all of this while working with real-world data, much as you would for a real data science project.
We’ll also cover how to how to install packages to extend R's functionality for working with dataframes, a crucial skill for extending your data science toolkit. And you’ll learn the basics of using R Studio, which is a popular free and open-source development environment that’s widely used in the R data science community, so that you can easily share projects.
When you’re done with this course, you will be confident with the basics of programming in R and you will have set up R Studio on your own machine so that you can easily create and share data science projects.
By the end of this course, you'll be able to:
Learn to Code With R
Introduction to Programming in R
Learn the basics of R, a popular programming language for data scientists.
Arithmetic Expressions and Variables in R
Learn more about the fundamentals of R syntax, how to assign and manipulate variables, and more.
Logical Expressions in R
Learn to write and work with logical expressions in your code.
Data Manipulation with R: Basics
Learn about the data analysis workflow in the context of R programming.
Guided Project: Install RStudio
Learn how to install and use RStudio, a free and open-source development environment for R.