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미시건 대학교의 Applied Social Network Analysis in Python 학습자 리뷰 및 피드백

4.6
별점
1,738개의 평가
286개의 리뷰

강좌 소개

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....

최상위 리뷰

NK

May 03, 2019

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

Sep 24, 2018

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.

필터링 기준:

Applied Social Network Analysis in Python의 279개 리뷰 중 26~50

교육 기관: Carl W

May 30, 2019

Month 5 was very nice. I enjoy networks and appreciate your presentation of the material. I would also like to thank all of those who worked to bring the specialization to life. This includes the lecturers, grad students, and mentors who devoted time to the class.

THANKS!!

교육 기관: 王玉龙

Oct 18, 2017

Eventhough the tutorial video is also switch to the teacher's face that make me stop the video to see the slide frame.But It's intuitive to understand the basic concept about the network with some exercise to enforce the knowledge. The final exercise is more intersting...

교육 기관: Praveen R

Dec 10, 2019

I learnt about networkx and its capabilities. The course introduces to many network algorithms and talks about concepts of centrality, page rank, etc. Good eye opener to all these concepts. The last assignment is very practical and challenging. Enjoyed the course.

Praveen

교육 기관: Dongliang Z

Jan 18, 2018

I enjoyed this course. This course is about the basic knowledge in network analysis. I do hope the lecturer can give more knowledge and application in network analysis. (Perhaps holding a series courses of Network Analysis in Python will be very good in the future!)

교육 기관: J W

Apr 21, 2018

Well put together. Quizzes test on material covered and assignments expand on it. There is still challenge and rigor, but it comes from understanding the concepts, not ambiguity and lack of instruction. This is one of the best online courses I've taken.

교육 기관: Nikolay S

Jan 02, 2019

The course and the tutor are great.

I learned how to create and manage network graphs using python with networkx. I was really satisfied from the last week assignment when I had to work with real-life example plus machine learning classifier.

교육 기관: Juan C E

Nov 11, 2017

Excellent course. Very clear explanations and materials. The assignments were not as difficult as in other courses of the specialization, and very helpful to understand the contents. I highly recommend this course and the specialization.

교육 기관: Manuel A

Aug 22, 2018

Very challenging and comprehensive course, also directly applicable to machine learning problems, as an example, the last assignment applies network knowledge to extract features and exploit them in predictive modelling problems

교육 기관: Alexander G

Feb 05, 2019

I got a bit the wrong impression from the title, but it was throughout the course very interesting to learn about Graphs. A welcome addition to the course would be a cheat sheet with the most important quantities.

교육 기관: Ling G

Sep 21, 2017

I like this class because the topic is interesting and the homework is not too hard but walks me through some important functionalities of NetworkX. The instructor is also pretty good at presentation as well.

교육 기관: Kedar J

Nov 16, 2018

Great intro course to graph theory and graph analysis using applied python networkx library. The course covers a number of theoretical topics. Would recommend using a local notebook along with the lectures.

교육 기관: Leonid I

Oct 18, 2018

Great course! Only one note: the online notebooks use an old version of networkx (v1.11), which is incompatible with the newer v2.2. Therefore, some trickery is required to read pickled networks locally...

교육 기관: Yaron K

Sep 21, 2017

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.

교육 기관: João R W S

Oct 07, 2017

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!

교육 기관: Nitin k

May 03, 2019

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.

교육 기관: Jingting L

Sep 24, 2018

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.

교육 기관: Christos G

Sep 18, 2017

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.

교육 기관: Dan S

Feb 25, 2018

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.

교육 기관: Brian L

Apr 18, 2018

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.

교육 기관: Spencer R

Mar 28, 2020

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.

교육 기관: Nick P

Oct 08, 2017

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

교육 기관: Korkrid A

Sep 27, 2017

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.

교육 기관: Servio P

Nov 18, 2017

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.

교육 기관: Saurabh S

Feb 19, 2018

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.

교육 기관: Nussaibah B R S

Jun 02, 2019

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.