Data Science: Wrangling

By: Harvard University
Free
Beginner, Certificate,
Duration: 8 Weeks

Learn to process and convert raw data into formats needed for analysis. 

In this course, part of our Professional Certificate Program in Data Science, we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.

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Course ByInstructor
Harvard UniversityRafael Irizarry

Course Details

In these cases, the first step is to import the data into R and tidy the data, using the tidyverse package. The steps that convert data from its raw form to the tidy form is called data wrangling.

This process is a critical step for any data scientist. Knowing how to wrangle and clean data will enable you to make critical insights that would otherwise be hidden.



What you will learn?

  • Importing data into R from different file formats
  • Web scraping
  • How to tidy data using the tidyverse to better facilitate analysis
  • String processing with regular expressions (regex)
  • Wrangling data using dplyr
  • How to work with dates and times as file formats, and text mining

Other Details

Course Instructor

Rafael Irizarry: Professor of Biostatistics, T.H. Chan School of Public Health

Check Course Content, Faqs, Rating and other important information about this course.

Details here


Disclaimer

We have tried to provide the best updated information about this Data Science: Wrangling course. However, if you find this course is not available or if there are any changes to this free course of Data Science: Wrangling then do let us know. Our team will make the necessary changes.



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