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Applied Social Network Analysis in Python No ratings yet.

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Applied Social Network Analysis in Python

Created/Published/Taught by:
University of Michigan
Daniel Romero

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Free? Partially: Some Free Content, Some Paid

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$0.00 - $73.00

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

From Coursera:

“This course will introduce the learner to network modelling through the networkx toolset. Used to model knowledge graphs and physical and virtual networks, the lens will be social network analysis. The course begins with an understanding of what network modelling is (graph theory) and motivations for why we might model phenomena as networks. The second week introduces the networkx library and discusses how to build and visualize networks. The third week will describe metrics as they relate to the networks and demonstrate how these metrics can be applied to graph structures. The final week will explore the social networking analysis workflow, from problem identification through to generation of insight.”

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

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