Getting and Cleaning Data

Learn how to gather and clean data from a variety of sources. This is the third course in the Johns Hopkins Data Science Specialization.

About The Course

Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.

Frequently Asked Questions

How do the courses in the Data Science Specialization depend on each other?
We have created a handy course dependency chart to help you see how the nine courses in the specialization depend on each other.

Will I get a Statement of Accomplishment after completing this class?
Yes. Students who successfully complete the class will receive a Statement of Accomplishment signed by the instructor.

What resources will I need for this class?
Students must have an active GitHub account and the latest version of R and RStudio installed.

How does this course fit into the Data Science Specialization?
This is the third course in the track. We strongly recommend that you first take The Data Scientist's Toolbox and R Programming.

Recommended Background

Data Scientist’s Toolbox, R Programming