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”.

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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.

This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

- Data Science: Foundations using R Specialization

- Data Science Specialization
What You Will Learn

- Understand common data storage systems

- Apply data cleaning basics to make data "tidy"

- Use R for text and date manipulation

- Obtain usable data from the web, APIs, and databases

Syllabus

WEEK 1

In this first week of the course, we look at finding data and reading different file types.
WEEK 2

This week the primary goal is to introduce you to the most common data storage systems and the appropriate tools to extract data from web or from databases like MySQL.
WEEK 3

This week the lectures will focus on organizing, merging and managing the data you have collected using the lectures from Weeks 1 and 2.
WEEK 4

This week we finish up with lectures on text and date manipulation in R. In this final week we will also focus on peer grading of Course Projects.