Introduction to the Tidyverse
- Offered byCoursera
Introduction to the Tidyverse at Coursera Overview
Duration | 8 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to the Tidyverse at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 1 of 5 in the Tidyverse Skills for Data Science in R Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level F'amiliarity with the R programming language
- Approx. 8 hours to complete
- English Subtitles: English
Introduction to the Tidyverse at Coursera Course details
- 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.
- If you are new to data science, the Tidyverse ecosystem of R packages is an excellent way to learn the different aspects of the data science pipeline, from importing the data, tidying the data into a format that is easy to work with, exploring and visualizing the data, and fitting machine learning models. If you are already experienced in data science, the Tidyverse provides a power system for streamlining your workflow in a coherent manner that can easily connect with other data science tools.
- In this course it is important that you be familiar with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course.
Introduction to the Tidyverse at Coursera Curriculum
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
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 Study #1: Health Expenditures
Case Study #2: Firearms
Project: Organizing a New Data Science Project
Introduction to the Tidyverse at Coursera Admission Process
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