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Introduction to R

via Datacamp

Overview

Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

In Introduction to R, you will master the basics of this widely used open source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis. Oracle estimated over 2 million R users worldwide in 2012, cementing R as a leading programming language in statistics and data science. Every year, the number of R users grows by about 40%, and an increasing number of organizations are using it in their day-to-day activities. Begin your journey to learn R with us today!

Syllabus

Intro to basics
-Take your first steps with R. In this chapter, 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.

Vectors
-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.

Matrices
-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 understand how to do basic computations with them. You will analyze the box office numbers of the Star Wars movies and learn how to use matrices in R. May the force be with you!

Factors
-Data often falls into a limited number of categories. For example, human hair color can be categorized as black, brown, blond, red, grey, or white—and perhaps a few more options for people who color their hair. In R, categorical data is stored in factors. Factors are very important in data analysis, so start learning how to create, subset, and compare them now.

Data frames
-Most datasets you will be working with will be stored as data frames. By the end of this chapter, you will be able to create a data frame, select interesting parts of a data frame, and order a data frame according to certain variables.

Lists
-As opposed to vectors, lists can hold components of different types, just as your to-do lists can contain different categories of tasks. This chapter will teach you how to create, name, and subset these lists.

Reviews

3.7 rating, based on 13 reviews

Start your review of Introduction to R

• Gregory J Hamel ( Life Is Study) completed this course.

Introduction to R is one of several free introductory level courses offered by DataCamp--an education platform for learning data science skills with a heavy focus on interactive coding exercises. The intro to R course is the first for 23 courses in DataCamp's...
• Antonio Serrano
12

Antonio Serrano completed this course, spending 4 hours a week on it and found the course difficulty to be easy.

I took the course "Writing Functions in R" at DataCamp. It was pretty good and I was very satisfied with the contents. The teachers were both excelent. But problems came when I tried to cancel my subscription. First I did it from the account settings...
• Anonymous

Anonymous completed this course.

Course was good but after i cancelled my membership they reactivated it 3 months later and charged me. I think they reactivate cancelled memberships as standard practice, easy for them if you used paypal.
• Anonymous

Anonymous completed this course and found the course difficulty to be easy.

This one is fine but I would not recommend next courses. I've canceled my subscription. Difficulty level seems to be not too consistent and some of the exercises are "out of context" without little of explanation of practical uses. I would also appreciate more videos.
• Anonymous
You only get 1 module for free, and it took me ~20 minutes to complete. It had a nice layout though, and I did like its approach to teaching.
• John Charles completed this course.

Hands down the best way to learn R. Extremely informative and clearly written lessons that provide the right balance of instruction and challenge. I would recommend DataCamp (and have) to anyone looking to learn the functional skills for a career in data science.
• Amalik Amriou completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.

Course for absolute beginners. Nothing more, nothing less. Basic but valuable.
This course is supposed to stand as an introduction to the full R course, so there is nothing surprising about the fact that it is very easy. Great to start.
• Claudia Scwz
9

Claudia Scwz completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.

This course is too easy! It could condense information a lot more and provide more practical examples. I guess it works if you're an absolute beginner and not at all familiar with any programming languages.
• Rodolphe Lampe completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.

This course is very well designed. You alternate between small videos (3mins) and small exercises through an interactive console. The teachers are experts in their fields and the video and audio are professional (compared to many other courses).
I truly enjoy Datacamp, I use it quite often.
To be honest, I post this advice because I received a mail from Datacamp asking me to do it, probably spotting that I'm an happy user. But I have nothing to win about it so this post is honest and I hope that anyone looking to learn R will follow this course, it's a good choice.
• Anonymous

Anonymous completed this course.

Datacamp classes give you a really nice walk through of the concepts with coding examples in the language with talks in between sections that provide a clear overview of the topic.

You're not going to be an expert after taking a section but will know where to look and also build on familiarity with the language. Much better than just reading about code in a textbook or taking on a huge project with no idea where to start.
• Anonymous

Anonymous completed this course.

Great course to start with R in data science. I'm 5 courses in at this point and love the DataCamp model of using video and coding exercises together. For me, it is the best tool out there.
• Kaya Lee completed this course, spending 2 hours a week on it and found the course difficulty to be easy.

A great course to learn multiple forms of data as an initial step of R programming.
It only took 4 hours to go through all the course.
• Monal Jain

Monal Jain completed this course.

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