R Basics for Data Analysis Path

R is a powerful programming language widely used for statistical computing. Its popularity is due, in part, to how useful it is at every stage of the data analysis process.

In this path, you’ll explore the basics of R, work through specialized data processing with strings and dates, and much more. R is in-demand, heavily supported by the community, exceptionally popular, and often associated with lucrative salaries.

Learn the basics of R programming at your own pace and from the comfort of your home.

Learn about packages and why they are essential in any data analysis process
Explore how to use and install RStudio to improve your data analysis workflow
LIdentify data structures such as vectors, lists, and DataFrames
Reveal how to repeat code efficiently with iteration

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What You’ll Learn

You’ll discover how to perform calculations using common arithmetic operators. You’ll also be able to enhance your resume, expand your skill set with this R Basics for Data Analysis path and overall develop new skills that you can use immediately.

Master control flow and iterations, learn advanced data processing, and discover how to use data structures in R. This path will help you acquire foundational knowledge in R to set you up for future learning both here at Dataquest and out in the field.

Here’s a list of skills you’ll learn in this path:

R programming syntax basics
Variable use and naming rules
Performing calculations using arithmetic operators
Creating and indexing a data structures
Performing operations over a data structure

Using control flow with if-else statements
Repeating your code efficiently with iteration
Using functions and writing your own functions
Manipulating strings from the stringr and lubridate packages

R programmers average $112,653 per year according to Glassdoor.

Data Analyst roles are slated for 25% job growth between 2019 and 2029.

R is purpose-built and uniquely designed for data analysis and statistical tasks.

How Our R Basics for Data Analysis Path Works

Data is everywhere. There are tremendous amounts of data in social media platforms, your favorite streaming services, banking, sales pipelines, emails—the list goes on. It’s the inescapable reality of the world today. However, all this data is useless without data analysis. Large datasets need cleaning, analysis, interpretation, and visualization. That’s why we created this path: to teach you the fundamentals of R for data analysis.

Dataquest’s teaching style is unique. We take an interactive approach, which means you learn by doing, not by watching. You’ll complete dozens of relevant practice problems using real code. Additionally, most courses contain a project that helps tie all the concepts together.

Our partnership approach also sets us apart. Leverage our in-depth support tools and thriving community for help throughout your studies.

Here’s a quick glance at this skill path:

This skill path consists of the four courses listed below, which cover the fundamentals of R and data analysis.
You’ll write real code with dozens of practice problems to validate and apply your skills.
At the end of each course, you’ll complete a guided project to reinforce your new knowledge and boost your interview-ready portfolio.
When you complete the course, you’ll receive a certificate that you can share with your professional network.
Once you master the fundamentals of R, you’ll be ready for more advanced courses.
Engage with our friendly community of R programmers, get feedback on your projects, and keep building your skills.

Enroll in this skill path to learn R Programming today!

R Basics for Data Analysis Path Course List

Introduction to Data Analysis in R
Learn R programming syntax basics and data types, and perform calculations using common arithmetics operators.

Data Structures in R
Learn how to create a data structure, how to index a data structure, and how to perform operations over a data structure.

Control Flow, Iteration and Functions in R
Learn how to use control flow with if-else statements, how to repeat your code efficiently with iteration, and how to use functions and write your own functions.

Specialized Data Processing in R
Strings and Dates: Learn how to manipulate strings from the stringr package, how to manipulate strings from the lubridate package, and how to use the map function from the purrr package.

Who Is This R Basics for Data Analysis Path For?

Whether you are a mid-career manager looking upskill, a beginner or a C-suite professional wanting to develop their career in a fast-growing field this path is perfect for you.

Anyone seeking an introduction to a powerful computer programming language
People interested in using R to analyze their own data, like their personal finances
Professionals looking to add another programming language to their skill set
Students looking to level up their data analysis skills for academic papers — or to be ready for a new career
Small business owners interested in analyzing their data to make important business decisions
Anyone interested in a career in data analysis
Anyone who wants to build a data analysis portfolio using real data

Qualify for In-demand Jobs in Data Analysis

Data analysts are key players in the business world, and they work with massive amounts of data in their roles. They’ll convert this data into valuable insights to enable executives and stakeholders to make informed decisions backed by quality information.

R Data Scientist
Data Analyst
Business Analyst
Clinical Data Analyst with R

Research Analyst
Financial Data Analyst
Open Source Analyst
Marketing Analyst

R Programmer
Junior Data Analyst
Operations Data Analyst
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