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Tidyverse Fundamentals with R

Experience the whole data science pipeline, from importing and tidying data to wrangling and visualizing data to modeling and communicating with data. Gain exposure to each component of this pipeline from a variety of different perspectives in this tidyverse R track. You’ll start by exploring the fundamentals of the tidyverse, a collection of data science tools within R. Here, you’ll learn how to use the tidyverse to analyze and visualize your own data. You’ll cover how to reshape data with tidyr, and how to complete linear regressions in a tidy framework. As you progress, you’ll use your skills and knowledge to perform analysis on real data sets, learning how to use tidyverse tools to visualize and communicate your findings. By the time you finish, you’ll have explored several tools in the tidyverse and have the confidence to work with data sets using these tools.

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1
R
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

David Robinson Headshot

David Robinson

Principal Data Scientist at Heap

2
R
Reshaping Data with tidyr

Transform almost any dataset into a tidy format to make analysis easier.

4 hours

Jeroen Boeye Headshot

Jeroen Boeye

Machine Learning Engineer @ Faktion

3
R
Dr. Semmelweis and the Importance of Handwashing

Reanalyze the data behind one of the most important discoveries of modern medicine: handwashing.

2 hours

Jasmin Ludolf Headshot

Jasmin Ludolf

Data Science Content Developer, DataCamp

4
R
Modeling with Data in the Tidyverse

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

4 hours

Albert Y. Kim Headshot

Albert Y. Kim

Associate Professor of Statistical & Data Sciences, Smith College

5
R
Communicating with Data in the Tidyverse

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

4 hours

Timo Grossenbacher Headshot

Timo Grossenbacher

Head of Newsroom Automation at Tamedia

6
R
Categorical Data in the Tidyverse

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

4 hours

Emily Robinson Headshot

Emily Robinson

Senior Data Scientist, Game Data Pros

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