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Вернуться к Applied Social Network Analysis in Python

Отзывы учащихся о курсе Applied Social Network Analysis in Python от партнера Мичиганский университет

Оценки: 2,558
Рецензии: 432

О курсе

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....

Лучшие рецензии


2 мая 2019 г.

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.


23 сент. 2018 г.

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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101–125 из 425 отзывов о курсе Applied Social Network Analysis in Python

автор: Dhananjai S

11 июня 2019 г.

One of the best courses on social network analysis. Professor Daniel Romero did an excellent job explaining the contents.

автор: Varga I K

9 мар. 2019 г.

It was great introducing the networks, but I found most of the assignments too straightforward except for the last weeks.

автор: Mile D

20 дек. 2017 г.

Excellent explanations and examples. Recommended text to read was also very helpful. Thanks for providing this course!!!

автор: Sarah H H

3 июня 2019 г.

i found this course to be fun and straightforward. The assignments were directly aligned to instruction. Great course!

автор: Christian P

29 дек. 2019 г.

Excellent, well taught and in-depth programming exercises. I really got my hands into programming with networkx here.

автор: Oscar J O R

15 окт. 2017 г.

A really good course. Notebooks could be very useful to practice and maybe more exercises(not graded) with real data.

автор: BHAVRAAJ S 1

4 июня 2020 г.

But why am i not getting certififcate of completion.I need it with tthe course which holds more value than learning

автор: Vladimir B

17 окт. 2021 г.

Great course. Some of the best assignments I've had the pleasure (and frustration) of doing. This prof is amazing.

автор: Slavisa D

9 июня 2019 г.

Very helpful, I didn't know anything about graphs, networks modelling and the NetworkX package before this course.

автор: Juan M

31 мая 2020 г.

Nice, delves on graph theory in quite an intuitive way, with exercises on Python. Can be recommended to a friend

автор: Yunhong H

23 мар. 2019 г.

Great course. The lectures are taught clearly. The knowledge gained in this course is very useful in real world.

автор: Karamcheti S R H

9 дек. 2020 г.

Very much satisfied with the course. Explanation is good project is very useful can be shown off in cv/ resume

автор: Iurii S

16 февр. 2018 г.

A great introduction to network analysis. Assignments are easy, but provide a good first glimpse at the topic.

автор: Darren

24 сент. 2017 г.

The best course I had on coursera ever, it really broaden my scope of knowledge. It worth waiting so much time

автор: Phillip L C

25 дек. 2018 г.

Just the greatest class to sum up what is going on in the crazy network media and using what we have learned.

автор: Yashaswa V

12 сент. 2021 г.

Intuitive last module of the specialization. Loved the content an could relate to them in practical way too.

автор: Adryan R A

3 мая 2021 г.

This is one of the most usefull course ive taken. Its really usefull and gave lots of insight about Analysis

автор: Diego T B

11 дек. 2018 г.

very useful and engaging. A was hoping a very different scope on the course but this approach did very well.

автор: Vivek R N

31 авг. 2020 г.

Really amazing course. The instructor is really nice and he explained the concepts in a really nice manner.

автор: Fernando M

31 авг. 2020 г.

Great course. I enjoyed the whole specialization I am very grateful with Coursera and Michigan University.

автор: Daniel B

2 апр. 2019 г.

Great introduction to social graph analysis, along with a very useful and popular Python package NetworkX.

автор: Edilson S

25 нояб. 2019 г.

Perfect Course! Exactly what I was looking for to deep my understanding in Graph Theory and Practice!

автор: Michal C

16 окт. 2017 г.

The course was interesting and valuable . Videos were clear and well organized.

I enjoyed studding it.

автор: César G C

10 мар. 2022 г.

Great introduction to social network analysis. Well explained lectures and interesting assignments.

автор: Aya

26 февр. 2019 г.

The course covered many relevant topics and was very easy to follow and apply to the real world.