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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

4.7
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Оценки: 2,505
Рецензии: 421

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

NK
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.

JL
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.

Фильтр по:

126–150 из 411 отзывов о курсе Applied Social Network Analysis in Python

автор: Landon M L

24 окт. 2017 г.

Good instruction because the explanation with some good examples that improve my comprehension.

автор: Wenlei Y

23 нояб. 2019 г.

This course really opens my eye, providing a new standpoint from which we visualize "network".

автор: Ivan S F

2 июня 2019 г.

Very very good course. It provides a brief but comprehensive introduction to network analysis.

автор: Benjamin R

9 июня 2018 г.

Very good insights into social network analysis. I particularly liked the final assignment.

автор: Rocco C

9 окт. 2017 г.

Very interesting course, thank you. The assignments could have been a bit more challenging.

автор: Long T B

27 окт. 2020 г.

I really appreciate Coursera for offering this course. It is very valuable to my research.

автор: Estella C

30 июля 2020 г.

Very practical course! Explained all the concepts very clear and with meaning examples.

автор: David T

4 янв. 2021 г.

I enjoyed the classes in this specialization. I felt that I have learned a great deal.

автор: Parikshit A D

3 мая 2020 г.

Best Course I have seen, learnt a lot about something to which I was completely new!!!

автор: Мирзабекян А В

9 авг. 2018 г.

One of the most interesting and challenging courses in specialization, in my opinion.

автор: Hiroki U

30 нояб. 2020 г.

Assignment of week4 was tough, but interesting.

Thanks for making such a good course.

автор: Reed R

2 мар. 2018 г.

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

автор: Rajesh R

7 февр. 2018 г.

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

автор: Carlos S

8 окт. 2017 г.

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

автор: Krzysztof K

5 нояб. 2020 г.

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

автор: Ricardo J M S

1 июня 2020 г.

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

автор: Ferdinand C

13 авг. 2020 г.

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

автор: Nicolás S

3 янв. 2021 г.

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

автор: Vighneshbalaji

28 апр. 2020 г.

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

автор: Chanaka S

1 авг. 2020 г.

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

автор: Amila R

30 сент. 2019 г.

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

автор: Roberto L L

26 мар. 2019 г.

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

автор: 高宇

2 дек. 2018 г.

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

автор: Thaweedet

15 авг. 2018 г.

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

автор: Mischa L

6 янв. 2018 г.

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