Learn to receive imperfect data, clean it, prepare it, and put it to work

 

To work with data, a data wrangler often has to synthesize many sources of data, in a variety of different formats, and often with missing, corrupt, or otherwise imperfect data. Preparing your data, or "cleaning" it is one of the most time-consuming and dry tasks a data wrangler has to deal with, but also one of the most important. In this course, you'll pretend to receive some imperfect data, then prepare it for use, and use it to answer some simple questions.