Introduction to Programming 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.
In this free introductory course on R, you’ll go hands-on with R for data science, learning critical R concepts such as matrices, vectors, lists, and more, and 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.
You will also learn how to update variables, work with different kinds of data, and how to import data into R and save it as a dataframe. 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 be ready to build your own unique data science projects (and move on to our intermediate R course).
By the end of this course, you'll be able to:
Learn to Program using R
Introduction To Programming in R
Learn the basics of R, a popular programming language for data scientists.
Working with Vectors
Learn how to index, manipulate, and perform calculations on vectors, important data structures in R.
Working with Matrices
Learn how to create, index, and manipulate matrices, important data structures in R.
Working with Lists
Learn how to create and manipulate lists.
Working With DataFrames
Learn how to create and manipulate DataFrames for data analysis in R.
Learn how to install and use RStudio, a free and open-source development environment for R.