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.
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.
创建者 Wei Wu•
Dec 09, 2018
This is by far my favorite Coursera course - well organized contents and intuitive example!
创建者 Jose Plana•
Dec 08, 2018
Social Network was completely new to me and I found this course provided basic and more detailed information about the matter, and also enough documentation to continue learning. I see there is much more to learn, but the course was a great introduction.
Dec 05, 2018
Dec 02, 2018
Very Nice Coursera! It lead me to reknow the relations among the worrld.
创建者 Steffen Heinz•
Nov 21, 2018
Course was ok, the assignments are not too difficult. I wish the course would provided more insights and discussions of the presented metrics of centrality though.
创建者 Ayon Banerjee•
Nov 20, 2018
Nice course. Well presented.
创建者 Shashi Prakash Tripathi•
Nov 17, 2018
This was wonderful course in terms of content and content delivery. Prof was really nice. His pace was very good.
创建者 Kedar Joshi•
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.
创建者 Anad Krishnamoorthy•
Nov 16, 2018
Good Content! And the assignments were just right to augment effective learning.
创建者 David McNay•
Nov 15, 2018
This is hands down the best taught course in the speciality. The instructor explains concepts in the videos clearly and the assignment questions are structured and interesting. Do note that the assignment in week 4 does pull together the whole specialisation in a real world problem, so if you aren't taking the whole speciality you will need a knowledge of Pandas and SKLearn. Personally I thought it was pitched at just the right level because the ML work is just enough to have to go through the process, without any complicated feature optimisation.
Only wish the other courses worked as well as this one.