Chevron Left
Applied Social Network Analysis in Python に戻る

ミシガン大学(University of Michigan) による Applied Social Network Analysis in Python の受講者のレビューおよびフィードバック

4.7
2,334件の評価
387件のレビュー

コースについて

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....

人気のレビュー

NK
2019年5月2日

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.

JL
2018年9月23日

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.

フィルター:

Applied Social Network Analysis in Python: 126 - 150 / 376 レビュー

by Reed R

2018年3月2日

Well taught and in a field which is not covered by many other data science curricula

by Rajesh R

2018年2月7日

Excellent course to understand various networking principles and analyszng the same.

by Carlos S

2017年10月8日

Great introduction to network theory and applications using Python Networkx library.

by Krzysztof K

2020年11月5日

Very informative and useful content was presented in very easy to understand way.

by Ricardo J M S

2020年6月1日

It is the best course of the 5 courses of the specialitation. I strongly recommend

by Ferdinand C

2020年8月13日

Brilliant instructor! I really learned a great deal from this course. Thank you

by Nicolás F S C

2021年1月3日

Nice topic to learn! Good materiales and tools were providade in thsi course

by Vighneshbalaji

2020年4月28日

Very Useful. I learned a lot. Thanks to Coursera and University of Michigan

by Chanaka S

2020年8月1日

Lecture is God To Me The Person Who has Good Knowledge then easy to study

by Amila R

2019年9月30日

Good starting point for those who want ro learn social network analysis.

by Roberto L L

2019年3月26日

It was a wonderful course, linked network's models and machine learning.

by 高宇

2018年12月2日

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

by Thaweedet

2018年8月15日

Great, You will to learn how to develop feature for social network data

by Mischa L

2018年1月6日

Great course. Very good homework assignments, but somewhat on easy side

by Rui

2017年10月11日

very good introductory course for social network analysis using Python.

by Dirisala S

2019年7月22日

The have lot of stuff to learn. It will definitely enhance your skill.

by Dibyendu C

2018年10月19日

Well structured and quality lecture content with excellent assignments

by Liran Y

2018年5月20日

Interesting and fun. Daniel's lecturing style is clear and enjoyable.

by Chiau H L

2019年4月4日

Awesome course!!! Helped me a lot to get started with graph analysis

by Keqi L

2019年4月14日

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

by Kai H

2018年11月8日

Good course, may be better if offer more practice and application.

by Tatek E

2020年3月23日

Excellent presentation, exercise and reading materials. Thank you

by wenzhu z

2018年2月22日

very clear logic, and will always wrap up at the end of the class

by 杨志陶

2020年5月17日

A practical way to learn social network analysis. Great course!

by Renzo B

2019年9月23日

I learned a lot of things that I can apply to my line of work.