Skip to main content
HomeR

Track

Data Analyst in R

Certification available
4.6+
20 reviews
From exploratory data analysis with dplyr to data visualization with ggplot2—gain the career-building R skills you need to succeed as a data analyst!
Start Track for Free

Included withPremium or Teams

R36 hours28,888

Create Your Free Account

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.
Group

Training 2 or more people?

Try DataCamp for Business

Loved by learners at thousands of companies

Certification badge

Certification Available

By

Industry recognized certifications help you stand out and prove your skills. Prepare for certification by completing this track.

Included with Premium
Included with PremiumLearn more

Track Description

Data Analyst in R

Master R for Real-World Data Analysis

Become a data analyst and advance your career by mastering R, the leading programming language for statistical computing and data analysis. In this Track, you'll learn how to import, clean, manipulate, and visualize data using R's powerful packages and libraries, including dplyr, ggplot2, and the tidyverse. Through hands-on exercises with real-world datasets, you'll develop the essential skills that employers look for in data analysts.

Build Your Data Analysis Toolkit

Progress from R basics to advanced data analysis techniques as you learn to:
  • Clean, transform, and manipulate data using dplyr and tidyverse packages
  • Create compelling data visualizations with ggplot2
  • Perform exploratory data analysis to uncover patterns and trends
  • Join and combine data from multiple sources
  • Apply statistical methods for hypothesis testing and sampling

Solve Real Business Problems with R

Apply your skills by working on projects that reflect the daily challenges faced by data analysts. Analyze customer behavior, identify market trends, and provide data-driven insights to stakeholders. By completing this Track, you'll have a portfolio of projects demonstrating your ability to tackle real-world data analysis tasks using R.

Designed for Beginners and Experienced Analysts Alike

Whether you're new to programming or looking to upskill, this Track is designed to help you succeed. With no prior coding experience required, you'll start by learning the fundamentals of R programming before diving into more advanced data analysis techniques. Experienced analysts will benefit from the Track's focus on industry-standard tools and best practices.

Why R for Data Analysis?

R has become the go-to language for data analysis due to its powerful statistical capabilities, extensive package ecosystem, and active community support. Its open-source nature and cross-platform compatibility make it accessible to everyone, while its flexibility allows analysts to tackle complex data challenges. As more organizations adopt R for their data analysis needs, mastering R skills can open up exciting career opportunities.

Launch Your Data Analysis Career

Upon completing this Track, you'll be ready to:
  • Apply for data analyst roles across industries
  • Collaborate effectively with data science teams
  • Make data-driven decisions to solve business problems
  • Communicate insights through compelling visualizations and reports
  • Continue learning and growing as a data professional

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to R

    Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

  • Course

    2

    Introduction to the Tidyverse

    Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

  • Project

    bonus

    Analyze the Popularity of Programming Languages

    Analyze the popularity of programming languages over time based on Stack Overflow data.

  • Course

    5

    Joining Data with dplyr

    Learn to combine data across multiple tables to answer more complex questions with dplyr.

  • Course

    10

    Sampling in R

    Master sampling to get more accurate statistics with less data.

  • Course

    11

    Hypothesis Testing in R

    Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Data Analyst in R
9 Courses
Track
Complete

Earn Statement of Accomplishment

Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review

Included withPremium or Teams

Enroll now

Don’t just take our word for it

*4.6
from 20 reviews
70%
25%
5%
0%
0%
  • Cedrick P.
    5 months

    Definitely instilled confidence that I can operate R on a fundamental level

  • Jon T.
    6 months

    Great courses to get you started on learning R.

  • Susana S.
    8 months

    Very good and well conceived. There are some minor queries on the help suggestion.

  • Thomas S.
    9 months

    Great content. Makes learning joy.

  • Héctor P.
    10 months

    A very good course in statisyics.

  • Nathan M.
    10 months

    Greatly enjoyed the course!

"Definitely instilled confidence that I can operate R on a fundamental level"

Cedrick P.

"Great courses to get you started on learning R."

Jon T.

"Very good and well conceived. There are some minor queries on the help suggestion."

Susana S.

FAQs

    Join over 16 million learners and start Data Analyst in R today!

    Create Your Free Account

    or

    By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.