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.
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
- 5 stars67.55%
- 4 stars23.66%
- 3 stars5.85%
- 2 stars1.60%
- 1 star1.31%
A very useful course. The audio quality of some lectures (especially those by the main instructor) was not good. This course completes the sister course of R programming and they work together.
I really liked this course and believe that my work, although seemingly noob-ish, will get much better as I see others works from the peer review and examples noted in the lessons.
This course is amazing! I have spent the majority of my time in R merely doing analytics. This course taught me the tools needed to go out and grab the data that I need for those analytics.
Actually, very interesting and helpful class. The one area around more complex structures (API, XML) warrants more attention, since I assume those are more dominant access methods.