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Applied Social Network Analysis in Python, University of Michigan

4.6
1,110 ratings
190 reviews

About this Course

This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem. This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....

Top reviews

By NK

May 03, 2019

This course is a excellent introduction to social network analysis. Learnt a lot about how social network works. Anyone learning Machine Learning and AI should definitely take this course. It's good.

By JL

Sep 24, 2018

It was an easy introductory course that is well structured and well explained. Took me roughly a weekend and I thoroughly enjoyed it. Hope the professor follows up with more advanced material.

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183 Reviews

By Henri

May 19, 2019

Great intro to networks; last assignment is challenging but is a good opportunity to put everything together (python+ML+Network).

By Vincenzo Timmel

May 16, 2019

Very good course! I was afraid going into this after going the rather bad "Text Mining". However, it was super fun, well done and informative!

By Magdiel Bruno do Nascimento Américo

May 12, 2019

ok

By Stephen

May 03, 2019

Good Course

By Nitin kumar

May 03, 2019

This course is a excellent introduction to social network analysis. Learnt a lot about how social network works. Anyone learning Machine Learning and AI should definitely take this course. It's good.

By Santiago Daniel Denegri

Apr 22, 2019

This class was an excellent introduction to network analysis, where concepts, metrics and purpose of application where provided in a clear and digestible manners. The instructor made the class very livable with topics that might have been too dry under different circumstances.

By Keary Parinis

Apr 21, 2019

Nice way to end the 5 course specialization. Brought together several machine learning and python skills that I learned in the previous courses. Instructor does a great job introducing new concepts with high level theory and intuitive examples. Course slides were superb and can serve as future reference material.

By Parul Sharma

Apr 20, 2019

good

By Ana Maria Lopez Moreno

Apr 15, 2019

Excellent course.

By Keqi Liu

Apr 14, 2019

Interesting slides and knowledge. e.g. Page rank is super cool!!!!