Link to Content:

Applied Plotting, Charting & Data Representation in Python

Created/Published/Taught by:

Coursera

University of Michigan

Christopher Brooks

Content Found Via:

Coursera

Free? Partially: Some Free Content, Some Paid

Cost Range:

$0.00 - $73.00

Tags: charts / data representation / data visualization / matplotlib / plotting / supervised learning

Difficulty Rating:

This course is #2 of 5 in the Applied Data Science with Python Specialization from the University of Michigan.

FromĀ Coursera:

“This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework. The third week will describe the gamut of functionality available in matplotlib, and demonstrate a variety of basic statistical charts helping learners to identify when a particular method is good for a particular problem. The course will end with a discussion of other forms of structuring and visualizing data.”

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

Go to Content: Applied Plotting, Charting and Data Representation in Python

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