DataQuest: R track
1. 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.
By the end of this course, you'll be able to:
- Understand The basis of syntax in the R programming language.
- Use comparison operators to make calculations.
- Work with basic data structures in R.
2. Intermediate R Programming
In our Intermediate Programming in R course, you will continue building your R data science skill set. We’ll take you beyond the basics to enhance your understanding of R, supercharge your workflow, do some pretty neat stuff along the way. To start off, you will learn how to use control structures in your R programming to control the flow of your code. Then, you will learn to work with vectorized functions to make the most of R's functionality. You will also learn how to use functions in your code to speed up your workflow and write better code to avoid common pitfalls. Next, you will learn about how to work with functionals and understand why they're suitable alternatives to loops, and you’ll get hands-on practice with single and multivariable functions. Towards the end of the course, you will learn the basics of working with strings and string manipulation as you analyze with real-world data from the World Cup. By the time you get to the end of this course, you’ll be quite comfortable with programming in R, and you’ll have built the fundamental skills you need to dive into a variety of unique data science projects of your own!
By the end of this course, you will be able to
- Use control structures.
- Use fuctionals in place of for-loops.
- Manipulate strings and dates.
- Use built-in and custom functions.