Data Analyst with R

Gain the career-building R skills you need to succeed as a data analyst! No prior coding experience required. In this track, you’ll learn how to import, clean, manipulate, and visualize data in R—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular R packages, including ggplot2 and tidyverse packages like dplyr and readr. You’ll also develop your data manipulation and exploratory data analysis skills by working with a wide range of real-world datasets, including everything from U.S. income data to global food consumption. You’ll then gain the statistical skills you'll need to perform hypothesis testing. Start this track, grow your R skills, and begin your journey to becoming a confident data analyst.

R36 hours9 courses

Create Your Free Account

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

Loved by learners at thousands of companies

Introduction to R

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

4 hours

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.

4 hours

Data Manipulation with dplyr

Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.

4 hours

Joining Data with dplyr

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

4 hours

Introduction to Statistics in R

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

4 hours

Introduction to Data Visualization with ggplot2

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

4 hours

Data Manipulation with R

Exploratory Data Analysis in R

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

4 hours

Sampling in R

Master sampling to get more accurate statistics with less data.

4 hours

Hypothesis Testing in R

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

4 hours

Loved by learners at thousands of companies

Instructors

Join over .css-1osvizq-TrackShowPage{color:#03ef62;}12,340,000 learners and start Data Analyst with R today!

Create Your Free Account

Join over 12,340,000 learners and start Data Analyst with R today!