Python Data Science Toolbox (Part 2)

Provided by:
9/10 stars
based on  1 review
Provided by:
Cost $29/mo
Start Date On demand

Course Details

Cost

$29/mo

Upcoming Schedule

  • On demand

Course Provider

DataCamp online courses
DataCamp is a young team of data analytics enthusiasts that provide free interactive data science and statistics education to the world. To us, the best way to learn is by doing; therefore at www.datacamp.com all our courses are provided through an online interactive learning platform tailored to hands-on experimentation in the browser and prepare you for jobs in the future.
DataCamp is a young team of data analytics enthusiasts that provide free interactive data science and statistics education to the world. To us, the best way to learn is by doing; therefore at www.datacamp.com all our courses are provided through an online interactive learning platform tailored to hands-on experimentation in the browser and prepare you for jobs in the future.
Provider Subject Specialization
Sciences & Technology
9 reviews

Course Description

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 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.
Python Data Science Toolbox (Part 2) course image
Reviews 9/10 stars
1 Review for Python Data Science Toolbox (Part 2)

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10/10 starsCompleted
  • 6 reviews
  • 6 completed
2 years, 3 months ago
The Python Data Science Toolbox course, which built on the basics of loop and functions, are really about putting together all the Python basics that we have learnt previously and apply them to data sets. Great course!
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