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Data Tidying and Importing with R
This course is part of Data Science with R Specialization.
Course Cost
Free course
Beginner
Skill Level
11 Hours
Self-paced lessons
This course teaches advanced data manipulation and transformation skills using R, focusing on tidyverse principles. Learn to use dplyr and tidyr for data cleaning, joining datasets, and converting between wide and long formats. Explore web scraping techniques and data importing strategies. Gain practical experience in preparing data for visualization and modeling, essential for data science and statistical analysis.
What you'll learn
Apply tidy data principles to manipulate and restructure data
Develop code to join datasets and perform basic web scraping
Use wide and long data formats, converting between them as needed
Implement data tidying techniques using dplyr and tidyr packages
Understand different data types and classes in R
Import data from various sources into R
Perform data recoding and transformation
Develop basic web scraping skills for data collection
Skills you'll gain
This course includes:
3 Hours PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
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There are 3 modules in this course
This course, part of the Data Science with R Specialization, focuses on data tidying and importing using R. Students will learn to apply tidy data principles to manipulate and restructure data using the tidyverse ecosystem, particularly dplyr and tidyr packages. The curriculum covers data transformation, joining datasets, and converting between wide and long formats. Participants will also explore web scraping techniques and considerations for ethical data collection. The course emphasizes practical skills in preparing data for visualization and future modeling, providing a strong foundation for advanced data science tasks. By the end of the course, students will be proficient in using R for efficient data manipulation and preparation, essential skills for any data science project.
Tidy Data
Module 1 · 4 Hours to complete
Importing + Recoding Data
Module 2 · 4 Hours to complete
Web Scraping and Programming
Module 3 · 3 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science with R Specialization
Payment options
Financial Aid
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Frequently asked Questions
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