Chevron Left
Вернуться к Applied Social Network Analysis in Python

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

4.7
звезд
Оценки: 2,244
Рецензии: 366

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:

101–125 из 355 отзывов о курсе Applied Social Network Analysis in Python

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: 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 S O J

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: Aya

26 февр. 2019 г.

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

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: 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: 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