Course Summary
Learn how to use the R tidyverse package to manipulate, clean, and visualize data in this comprehensive course.Key Learning Points
- Gain a thorough understanding of the tidyverse package and its components
- Learn how to manipulate and clean data using dplyr and tidyr
- Create visualizations using ggplot2 and other tidyverse tools
Job Positions & Salaries of people who have taken this course might have
- USA: $65,000 - $110,000
- India: INR 4,00,000 - INR 12,00,000
- Spain: €30,000 - €45,000
- USA: $65,000 - $110,000
- India: INR 4,00,000 - INR 12,00,000
- Spain: €30,000 - €45,000
- USA: $85,000 - $145,000
- India: INR 6,00,000 - INR 18,00,000
- Spain: €40,000 - €60,000
- USA: $65,000 - $110,000
- India: INR 4,00,000 - INR 12,00,000
- Spain: €30,000 - €45,000
- USA: $85,000 - $145,000
- India: INR 6,00,000 - INR 18,00,000
- Spain: €40,000 - €60,000
- USA: $70,000 - $120,000
- India: INR 4,50,000 - INR 13,00,000
- Spain: €35,000 - €50,000
Related Topics for further study
Learning Outcomes
- Ability to use tidyverse package to manipulate and clean data
- Ability to create visualizations using ggplot2 and other tidyverse tools
- Understanding of R programming language and its applications in data analysis
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of R programming language
- Familiarity with data analysis and manipulation concepts
Course Difficulty Level
IntermediateCourse Format
- Online and self-paced
- Video lectures and hands-on exercises
Similar Courses
- Data Analysis with R
- Data Visualization with ggplot2
- Data Manipulation with dplyr
Related Education Paths
Notable People in This Field
- Data Scientist at ThinkR
- Professor of Statistics at University of British Columbia
Related Books
Description
This course introduces a powerful set of data science tools known as the Tidyverse. The Tidyverse has revolutionized the way in which data scientists do almost every aspect of their job. We will cover the simple idea of "tidy data" and how this idea serves to organize data for analysis and modeling. We will also cover how non-tidy can be transformed to tidy data, the data science project life cycle, and the ecosystem of Tidyverse R packages that can be used to execute a data science project.
Knowledge
- D​istinguish between tidy and non-tidy data
- Describe how non-tidy data can be transformed into tidy data
- D​escribe the Tidyverse ecosystem of packages
- O​rganize and initialize a data science project
Outline
- Tidy Data
- About This Course
- Data Terminology
- Principles of Tidy Data
- Tidy Data Are Rectangular
- Tidy Data Benefits
- Rules for Storing Tidy Data
- Principles of tidy data quiz
- Tidy Data Rules Quiz
- From Non-Tidy –> Tidy
- Common problems with messy datasets
- Examples of untidy data
- Tidying untidy data
- Messy Data Quiz
- The Data Science Life Cycle & Tidyverse Ecosystem
- The Data Science Life Cycle
- Reading Data into R
- Data Tidying
- Data Visualization
- Data Modeling
- Data Science Project Organization & Workflows
- RStudio Projects
- File Paths
- The here package
- File Naming
- Project Template: Everything In Its Place
- Data Science Workflows
- File Naming and here Package Quiz
- Project Organizing Quiz
- Case Studies
- Case Study #1: Health Expenditures
- Case Study #2: Firearms
- Project: Organizing a New Data Science Project
Summary of User Reviews
Learn how to use Tidyverse for data analysis with this highly-rated course on Coursera.Key Aspect Users Liked About This Course
Many users praise the course for its clear and concise explanations of Tidyverse concepts.Pros from User Reviews
- Well-organized and easy to follow curriculum
- Experienced instructors with a strong understanding of Tidyverse
- Hands-on exercises and projects to reinforce learning
Cons from User Reviews
- Some users found the pace to be too slow
- Not suitable for advanced Tidyverse users
- Limited discussion of other data analysis tools
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