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Voltar para Applied Social Network Analysis in Python

Applied Social Network Analysis in Python, University of Michigan

4.6
836 classificações
147 avaliações

Informações sobre o curso

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....

Melhores avaliações

por 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.

por CG

Sep 18, 2017

Excellent tour through the basic terminology and key metrics of Graphs, with a lot of help from the networkX library that simplifies many, otherwise tough, tasks, calculations and processes.

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144 avaliações

por Wei Wu

Dec 09, 2018

This is by far my favorite Coursera course - well organized contents and intuitive example!

por Jose Plana

Dec 08, 2018

Social Network was completely new to me and I found this course provided basic and more detailed information about the matter, and also enough documentation to continue learning. I see there is much more to learn, but the course was a great introduction.

por 马一凡

Dec 05, 2018

great

por 高宇

Dec 02, 2018

Very Nice Coursera! It lead me to reknow the relations among the worrld.

por Steffen Heinz

Nov 21, 2018

Course was ok, the assignments are not too difficult. I wish the course would provided more insights and discussions of the presented metrics of centrality though.

por Ayon Banerjee

Nov 20, 2018

Nice course. Well presented.

por Shashi Prakash Tripathi

Nov 17, 2018

This was wonderful course in terms of content and content delivery. Prof was really nice. His pace was very good.

por Kedar Joshi

Nov 16, 2018

Great intro course to graph theory and graph analysis using applied python networkx library. The course covers a number of theoretical topics. Would recommend using a local notebook along with the lectures.

por Anad Krishnamoorthy

Nov 16, 2018

Good Content! And the assignments were just right to augment effective learning.

por David McNay

Nov 15, 2018

This is hands down the best taught course in the speciality. The instructor explains concepts in the videos clearly and the assignment questions are structured and interesting. Do note that the assignment in week 4 does pull together the whole specialisation in a real world problem, so if you aren't taking the whole speciality you will need a knowledge of Pandas and SKLearn. Personally I thought it was pitched at just the right level because the ML work is just enough to have to go through the process, without any complicated feature optimisation.

Only wish the other courses worked as well as this one.