Introduction to R for Data Science

This Introduction to R for Data Science course will teach you the R statistical programming language, the lingua franca of data science in this hands-on course.

Future Skills Lab - Introduction to R for Data Science

About This Course

R is rapidly becoming the leading language in data science and statistics. Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs.

This introduction to R programming course will help you master the basics of R. In seven sections, you will cover its basic syntax, making you ready to undertake your own first data analysis using R. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.

What makes this course unique is that you will continuously practice your newly acquired skills through interactive in-browser coding challenges using the DataCamp platform. Instead of passively watching videos, you will solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.

Enjoy!

What you’ll learn

  • Introductory R language fundamentals and basic syntax
  • What R is and how it’s used to perform data analysis
  • Become familiar with the major R data structures
  • Create your own visualizations using R

Course Syllabus

Section 1: Introduction to Basics
Take your first steps with R. Discover the basic data types in R and assign your first variable.

Section 2: Vectors
Analyze gambling behaviour using vectors. Create, name and select elements from vectors.

Section 3: Matrices
Learn how to work with matrices in R. Do basic computations with them and demonstrate your knowledge by analyzing the Star Wars box office figures.

Section 4: Factors
R stores categorical data in factors. Learn how to create, subset and compare categorical data.

Section 5: Data Frames
When working R, you’ll probably deal with Data Frames all the time. Therefore, you need to know how to create one, select the most interesting parts of it, and order them.

Section 6: Lists
Lists allow you to store components of different types. Section 6 will show you how to deal with lists.

Section 7: Basic Graphics
Discover R’s packages to do graphics and create your own data visualizations.

Meet the instructors

Course Staff Image #1

Filip Schouwenaars

Filip is the main course developer behind many of DataCamp’s interactive courses. His courses and tutorials were already taken by thousands of students across the world. DataCamp has trained more than 250,000 data scientists who’ve completed over 3.7 million interactive exercises.

Course Staff Image #2

Jonathan Sanito

Jonathan works as a content developer and project manager for Microsoft focusing in Data and Analytics online training. He has worked with trainings for developer and IT pro audiences, from Microsoft Dynamics NAV to Windows Active Directory. Before coming to Microsoft, Jonathan worked as a consultant for a Microsoft partner, implementing Microsoft Dynamics NAV solutions.

Start with Introduction to R for Data Science

You can enroll now for Introduction to R for Data Science at the DataChangers Academy! Please use your Windows Live ID email address to register at the DataChangers Academy if you want to obtain a certificate after finishing the courses.

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