FavoriteLoadingBookmark this content

DataCamp – Python for Data Science Toolbox (Part 2) No ratings yet.

Link to Content:
DataCamp Python for Data Science Toolbox Part 2

Created/Published/Taught by:
Hugo Bowne-Anderson
Francisco Castro
Yashas Roy

Content Found Via:

Free? Partially: Some Free Content, Some Paid

Cost Range:
$0.00 - $29.00

Tags: / / /
Content Type: /

Difficulty Rating:

No ratings yet.

Part 1 of this course can be found here: Python Data Science Toolbox Part 1

From DataCamp:

“In this second course in the Python Data Science Toolbox, you’ll continue to build your Python Data Science skills. First, you’ll enter the wonderful world of iterators, objects that you have already encountered in the the context of for loops without having necessarily known it. You’ll then learn about list comprehensions, which are extremely handy tools that form a basic component in the toolbox of all modern Data Scientists working in Python. You’ll end the course by working through a case study in which you’ll apply all of the techniques you learned both in this course as well as the prequel. If you’re looking to make it as a Pythonista Data Science ninja, you have come to the right place.”

This course consists of three chapters:

  1. Using iterators in PythonLand
  2. List comprehensions and generators
  3. Bringing it all together!

Recommended Prerequisites: Intro to Python for Data Science, Intermediate Python for Data Science, Python Data Science Toolbox (Part 1)

Go to Content: DataCamp – Python for Data Science Toolbox (Part 2)