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.
- 5 stars67.57%
- 4 stars23.61%
- 3 stars5.85%
- 2 stars1.61%
- 1 star1.33%
The course was very helpful & guided but since I don't have a strong coding background I felt myself getting lost often. It would be really helpful if there is some guidance in assignments.
I found the last project insufficiently explained. I was struggling in understanding what the task is. A bit more clear task description (as in Course 2) would be really appreciated.
This course provides an introduction of some important concepts and tools on a very important aspect of data science: cleaning and organizing data before any analysis. A must for any data scientist.
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.