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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
звезд
Оценки: 2,249
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.

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51–75 из 358 отзывов о курсе Applied Social Network Analysis in Python

автор: Yaron K

21 сент. 2017 г.

Excellent course. Lecturer clearly explains network analysis terms and algorithms with examples, and then shows how they are implemented by the Python networkX library. The assignments exercise their use.

автор: João R W S

6 окт. 2017 г.

Very good course! I've learned a lot both in theory and practical aspects. The final assignment worth to put all together with the skills learned in the other 4 courses of the specialization. Great job!

автор: Nitin K

3 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.

автор: Christos G

18 сент. 2017 г.

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.

автор: dan s

25 февр. 2018 г.

I loved this course. It was well taught and had excellent problem sets and quizzes to internalize the learning. The material is very relevant to the market today. I highly recommend it.

автор: Brian L

17 апр. 2018 г.

Really enjoyed the mathematical component of this course. It was fun to see how you could connect the graph theoretical components to the machine learning concepts from earlier courses.

автор: Sandilya M

18 нояб. 2020 г.

I have never imagined such detailed analysis can be done on a network, nx in python is really powerful package with so many powerful functions that can do ample of analysis at a whim.

автор: Francis J A

23 нояб. 2020 г.

Great introductory course on graph theory using Networkx. The instructor goes through each algorithm with step-by-step examples, and gives relevant examples at the end of each topic.

автор: Spencer R

28 мар. 2020 г.

Very helpful courses. I was able to review and got much better at some things I already knew like data visualization and was able to explore some new areas like network analysis.

автор: Luiz S

23 авг. 2020 г.

Basic yet informative course. The videos are well paced and the presenter is instructive. The exercises are well made, putting more enphasis on what was learned in the videos.

автор: Nick P

7 окт. 2017 г.

Interesting material and easy to follow. Assignments and quizzes were sufficiently challenging, but not too difficult that I spent entire weekends troubleshooting my code.

автор: Korkrid A

27 сент. 2017 г.

It's rare to find an amazing course in network analysis online, and I'm very glad to have taken this course and learn the art of network analysis for research purposes.

автор: Servio P

18 нояб. 2017 г.

This course contains many important concepts of Graph Theory and Network Analysis. The explanation is clear and neat. Also, the assignments are fun and comprehensible.

автор: Saurabh S

19 февр. 2018 г.

Very comprehensive course for introduction of social network analysis. Best part is every concept is covered in detail and how to implement using networkx library.

автор: Nussaibah B R S

2 июня 2019 г.

I found it hard sometimes to understand the concepts but this gave me quite an introduction on social network analysis and encouraged me to learn more about them.

автор: Jorge A S

27 февр. 2018 г.

Great explanations. The instructor is awesome and has good visual material. In-video quizzes keep you engaged during the lecture. I am very happy with the course.

автор: 谢仑辰

23 мар. 2018 г.

I really appreciate that you offer me such a great specialization of courses.Since I've finished the final course eventually, I should offer my gratitude to you.

автор: Fabrice L

23 нояб. 2017 г.

Very good class.

The lecturer is amazing!! The quizzes help you understand the concepts. The assignments are a little basic though.

Overall you learn a great deal.

автор: Punam P

25 апр. 2020 г.

Very nice platform to learn & enhance skill. Thanks to Prof. and team.. Also thanks to university and coursera platform for providing such a big platform to us.

автор: Morgan S

22 июля 2020 г.

Great introductory course to graph theory! Dr. Romero is one of the most engaging professors that I've had, both in-person and online. The assignments are fun.

автор: Jiaqi d

15 дек. 2019 г.

Really helpful. Get a basic idea of the social network and how to use python to analyze it. Will definitely dig deeper and see how it could relate to my work .

автор: Soh Y Z

16 нояб. 2020 г.

Clear explanation. Very well taught course. Will be good if the course also teaches us how to extract social network information from social media sites.

автор: Avulapati N

3 июля 2020 г.

A nice short course on Networks. This was one of the best courses I've taken on Coursera.

The course content, instructor and assignments are all amazing.

автор: Piyush V

29 янв. 2020 г.

All over the course is very relevant to what is a need in industry. Very nice video lectures, to the point and crisp. Material is quite informative too.

автор: M J

4 июня 2018 г.

An excellent course which is well planned and executed! If you're following the specialization, it's a welcome relief after the text analysis course.