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Introduction to R (beta)

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5 Hours13 Videos73 Exercises27,963 Learners6550 XP

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Course Description

With over 2 million users worldwide R is rapidly becoming the leading programming language in statistics and data science. Every year, the number of R users grows by 40%, and an increasing number of organizations are using it in their day-to-day activities.
In this introduction to R, you will master the basics of this beautiful open source language such as factors, lists and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.

  1. 1

    Intro to basics

    Free

    In this chapter, you will take your first steps with R. You will learn how to use the console as a calculator and how to assign variables. You will also get to know the basic data types in R. Let's get started!

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    Meet R
    50 xp
    Your first R script
    100 xp
    Documenting your code
    100 xp
    R as a calculator
    100 xp
    R's pros and cons
    50 xp
    Variable assignment (1)
    100 xp
    Variable assignment (2)
    100 xp
    Variable assignment (3)
    100 xp
    The workspace
    100 xp
    Basic Data Types
    50 xp
    Discover Basic Data Types
    100 xp
    Back to Apples and Oranges
    100 xp
    What's that data type?
    50 xp
    Coercion: Taming your data
    100 xp
  2. 2

    Vectors

    Free

    We take you on a trip to Vegas, where you will learn how to analyze your gambling results using vectors in R! After completing this chapter, you will be able to create vectors in R, name them, select elements from them and compare different vectors.

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  3. 3

    Matrices

    Free

    In this chapter you will learn how to work with matrices in R. By the end of the chapter, you will be able to create matrices and to understand how you can do basic computations with them. You will analyze the box office numbers of Star Wars to illustrate the use of matrices in R. May the force be with you!

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  4. 4

    Factors

    Free

    Very often, data falls into a limited number of categories.In R, categorical data is stored in factors. Given the importance of these factors in data analysis, you should start learning how to create, subset and compare them now!

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  5. 5

    Lists

    Free

    Lists, as opposed to vectors, can hold components of different types, just like your to-do list at home or at work. This chapter will teach you how to create, name and subset these lists!

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What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA

Join over 9 million learners and start Introduction to R (beta) today!

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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).