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Getting Started with Tidyverse

Dr. Karl Michel
In this project, you will learn about Tidyverse, a system of packages for data manipulation, exploration and visualization in the R programming language. R is a computer programming language, and it is also an open-source software often used among data scientists, statisticians, and data miners in their everyday work with data sets.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches data manipulation and visualization using R programming language, which are highly relevant to data scientists, statisticians, and data miners
Provides a strong foundation for beginners in data manipulation and visualization
Uses a multi-modal approach with videos, readings, and discussions, making learning more engaging
Taught by Dr. Karl Michel, who is a recognized expert in data manipulation and visualization
May require additional software or tools that are not readily available in all households or libraries

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Getting Started with Tidyverse with these activities:
Advanced R
Read Advanced R to gain a deeper understanding of the R programming language.
View R for Data Science: Import, Tidy, Transform,... on Amazon
Show steps
  • Get a copy of the book
  • Read the book and take notes
  • Complete the exercises in the book
Tidyverse Tutorials
Follow tutorials to learn the basics of the Tidyverse.
Browse courses on Tidyverse
Show steps
  • Find a tutorial on the Tidyverse
  • Go through the tutorial step-by-step
  • Complete the exercises and quizzes in the tutorial
Tidyverse Workshop
Attend a workshop to learn about the Tidyverse and its applications.
Browse courses on Tidyverse
Show steps
  • Find a Tidyverse workshop
  • Register for the workshop
  • Attend the workshop and participate in the activities
Five other activities
Expand to see all activities and additional details
Show all eight activities
Code Challenges
Solve coding challenges to improve your understanding of the Tidyverse.
Browse courses on R Programming
Show steps
  • Visit a coding challenge website or platform
  • Select a challenge related to the Tidyverse
  • Read and understand the challenge prompt
  • Write code to solve the challenge
  • Review your solution and make improvements as needed
Study Group
Join a study group to discuss concepts and work on projects together.
Browse courses on R Programming
Show steps
  • Find or create a study group
  • Meet regularly with your group
  • Discuss course material and work on assignments
Data Analysis Projects
Work on data analysis projects to apply your skills and gain real-world experience.
Browse courses on Tidyverse
Show steps
  • Find a dataset to work with
  • Clean and prepare the data
  • Analyze the data and draw conclusions
  • Present your findings
Contribute to Tidyverse
Contribute to the Tidyverse project to gain a deeper understanding of its inner workings.
Browse courses on Tidyverse
Show steps
  • Find an issue or feature request on the Tidyverse GitHub repository
  • Read the issue or feature request and understand the problem
  • Propose a solution and submit a pull request
Tidyverse Blog Post
Write a blog post about your experiences using the Tidyverse.
Browse courses on Tidyverse
Show steps
  • Choose a topic related to Tidyverse
  • Research and gather information on the topic
  • Write your blog post
  • Publish your blog post and share it with others

Career center

Learners who complete Getting Started with Tidyverse will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Machine Learning Engineers. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Machine Learning Engineers.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
A Data Analyst uses data to solve business problems and improve decision-making. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Data Analysts. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Data Analysts.
See salaries and explore the career path for Data Analyst
Data Scientist
A Data Scientist uses programming, statistics, and other techniques to uncover patterns in data and offer insights to help make informed decisions. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is widely used by Data Scientists. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Data Scientists.
See salaries and explore the career path for Data Scientist
Data Engineer
A Data Engineer builds and maintains data infrastructure. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Data Engineers. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Data Engineers.
See salaries and explore the career path for Data Engineer
Statistician
A Statistician uses statistical methods to analyze data and draw conclusions. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Statisticians. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Statisticians.
See salaries and explore the career path for Statistician
Financial Analyst
A Financial Analyst uses data to make investment decisions. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Financial Analysts. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Financial Analysts.
See salaries and explore the career path for Financial Analyst
Quantitative Analyst
A Quantitative Analyst uses data to make investment decisions. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Quantitative Analysts. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Quantitative Analysts.
See salaries and explore the career path for Quantitative Analyst
Operations Research Analyst
An Operations Research Analyst uses data to improve operational efficiency. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Operations Research Analysts. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Operations Research Analysts.
See salaries and explore the career path for Operations Research Analyst
Business Analyst
A Business Analyst uses data to identify and solve business problems. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Business Analysts. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Business Analysts.
See salaries and explore the career path for Business Analyst
Market Researcher
A Market Researcher uses data to understand consumer behavior. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Market Researchers. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Market Researchers.
See salaries and explore the career path for Market Researcher
Database Administrator
A Database Administrator maintains and manages databases. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Database Administrators. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Database Administrators.
See salaries and explore the career path for Database Administrator
Software Engineer
A Software Engineer builds and maintains software. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Software Engineers. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Software Engineers.
See salaries and explore the career path for Software Engineer
Web Developer
A Web Developer builds and maintains websites. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Web Developers. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Web Developers.
See salaries and explore the career path for Web Developer
Product Manager
A Product Manager manages the development and launch of new products. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Product Managers. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Product Managers.
See salaries and explore the career path for Product Manager
Data Visualization Analyst
A Data Visualization Analyst uses data to create visualizations that communicate insights. This course provides a foundation in Tidyverse, a system of packages in R programming language, which is often used by Data Visualization Analysts. The course covers data manipulation, exploration, and visualization, all of which are essential skills for Data Visualization Analysts.
See salaries and explore the career path for Data Visualization Analyst

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Getting Started with Tidyverse.
Cover image
R for Data Science
Save
Comprehensive guide to using R for data science. It covers all the essential topics, from data import and cleaning to data visualization and analysis. This book valuable resource for anyone who wants to learn how to use R for data science.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
R Packages
Save
Follow-up to R for Data Science. It covers more advanced topics, such as functional programming, data manipulation, and statistical modeling. This book valuable resource for anyone who wants to learn more about R.
R Packages
Paperback
Check
R Packages
Kindle Edition
Check
Cover image
Modern Data Visualization with R
Save
Practical guide to using R for data science. It covers a wide range of topics, from data import and cleaning to data visualization and analysis. This book valuable resource for anyone who wants to learn how to use R for data science.
Modern Data Visualization with R
Paperback
Check
Modern Data Visualization with R
Kindle Edition
Check
Cover image
Data Manipulation with R
Save
Comprehensive guide to data manipulation in R. It covers all the essential topics, from data import and cleaning to data transformation and aggregation. This book valuable resource for anyone who wants to learn how to manipulate data in R.
Data Manipulation with R (Use R!)
Paperback
$$$
Data Manipulation with R (Use R!)
Kindle Edition
$$$
Cover image
R Cookbook
Save
Collection of recipes for solving common problems in R. It covers a wide range of topics, from data import and cleaning to data visualization and analysis. This book valuable resource for anyone who wants to learn how to solve common problems in R.
R Cookbook: Proven Recipes for Data Analysis,...
Paperback
$$$
R Cookbook: Proven Recipes for Data Analysis,...
Kindle Edition
$$$
Cover image
The Art of Machine Learning
Save
Guide to the art of programming in R. It covers topics such as code style, debugging, and performance tuning. This book valuable resource for anyone who wants to learn how to write better R code.
The Art of Machine Learning: A Hands-On Guide to...
Paperback
$$
The Art of Machine Learning: A Hands-On Guide to...
Kindle Edition
$$
Cover image
R Graphics Cookbook
Save
Collection of recipes for creating beautiful and informative graphics in R. It covers a wide range of topics, from basic charts to complex visualizations. This book valuable resource for anyone who wants to learn how to create better graphics in R.
R Graphics Cookbook
Paperback
Check
R Graphics Cookbook
Kindle Edition
Check
Cover image
R Programming for Data Science
Save
Comprehensive guide to programming in R for data science. It covers all the essential topics, from data import and cleaning to data visualization and analysis. This book valuable resource for anyone who wants to learn how to program in R for data science.
R Programming for Data Science
Paperback
$$
Cover image
Effective Construction Project Delivery
Save
Comprehensive guide to data manipulation in R. It covers all the essential topics, from data import and cleaning to data transformation and aggregation. This book valuable resource for anyone who wants to learn how to manipulate data in R.
Effective Construction Project Delivery: Improving...
Paperback
$$$$
Cover image
An Introduction to Statistical Learning
Save
Comprehensive guide to machine learning in R. It covers all the essential topics, from supervised learning to unsupervised learning. This book valuable resource for anyone who wants to learn how to use R for machine learning.
An Introduction to Statistical Learning
Paperback
Check
An Introduction to Statistical Learning
Kindle Edition
Check
Cover image
Deep Learning with R
Save
Comprehensive guide to deep learning in R. It covers all the essential topics, from neural networks to deep learning models. This book valuable resource for anyone who wants to learn how to use R for deep learning.
Deep Learning with R
Paperback
Check
Deep Learning with R
Kindle Edition
Check
Cover image
The R Book
Save
Comprehensive reference guide to the R programming language. It covers all the essential topics, from basic syntax to advanced statistical techniques. This book valuable resource for anyone who wants to learn more about R.
The R Book
Hardcover
$$$
The R Book
Kindle Edition
$$$

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Time
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Coursera
Institution
Coursera Project Network
Instructor
Dr. Karl Michel
Good to know
Teaches data manipulation and visualization using R programming language, which are highly relevant to data scientists, statisticians, and data miners
Provides a strong foundation for beginners in data manipulation and visualization
Uses a multi-modal approach with videos, readings, and discussions, making learning more engaging
Taught by Dr. Karl Michel, who is a recognized expert in data manipulation and visualization
May require additional software or tools that are not readily available in all households or libraries
Share and help others discover this course.
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