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Introduction to Data Science in Python

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Introduction to Data Science in Python

Created/Published/Taught by:
University of Michigan
Christopher Brooks

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Free? Partially: Some Free Content, Some Paid

Cost Range:
$0.00 - $73.00

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Difficulty Rating:
Early Beginner 1
Advanced Beginner 0
Intermediate 0
Advanced Intermediate 0
Advanced 0

This course is #1 of 5 in the Applied Data Science with Python Specialization from the University of Michigan.

From Coursera:

“This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. The course will end with a statistics primer, showing how various statistical measures can be applied to pandas DataFrames. By the end of the course, students will be able to take tabular data, clean it,  manipulate it, and run basic inferential statistical analyses.”


Recommended Prerequisites: "intended for learners who have basic python or programming background….Minimal statistics background" required.

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