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.
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.
創建者 Hewawitharanage A H•
Feb 01, 2020
創建者 Parul S•
Apr 20, 2019
創建者 Akash G•
Mar 03, 2019
Aug 18, 2018
創建者 Magdiel B d N A•
May 12, 2019
創建者 David C•
Sep 21, 2017
This was, in general, a good course. The instructor was very clear in what he presented, and gave a good overview of Social Network Analysis. However, there were several issues with the AutoGrader that did not get fixed until late in the course and the PowerPoint slides for the lectures were also very late in getting posted (they were not available for most of the programming assignments). So, I think this course was launched a little early. Still, these are problems that you might expect to see the first time a course is taught and should not affect future students.
The bigger complaint I have on the course was that it was a very gentle introduction of the topic with only a quick overview of the subject. The lectures themselves concentrated more on a litany of various measures and metrics to characterize networks and could have benefited from a broader examination of real networks in the real world. One of the most interesting topics was a very quick overview of plotting for network diagrams, but this was never followed up with a programming assignment or other aspects to give us practice using the techniques described. This course would benefit from 2-4 additional weeks of material and more programming assignments, IMO. The network graphing lecture, for example, could have been reinforced with a peer-graded assignment to have us produce 3 or 4 types of graphs of various networks.
Overall, though, I was pleased with this course and the entire specialization. I would definitely recommend it to others.
創建者 John W•
Jun 11, 2019
This was a good course. I learned a good amount about network analysis and the python library networkx. I can envision using what I learned in my job. However, of the five courses in the Applied Data Science with Python Specialization I felt this was the weakest offering.
1. The Title. While the majority of the examples and exercises were focused on social networks, there's little in the course that is really specific to social networks. The course applies to any kind of network that can be loaded into networkx.
2. Trim the Process Descriptions. Too often the lecturer would say things like "Node A has degree of 3 because it is connected to three other nodes. Node B has a degree of 5 because it is connected to five other nodes. Node C has a degree of 4 because it is connected to four other nodes." For such a simple concept, that many examples aren't needed.
3. Provide On-Screen Example Files (my biggest gripe). In all of the previous courses, when the lecturer gave code examples on screen, there was a corresponding Jupyter notebook with those examples so the learner could follow along, and keep the notebook as a handy refresher of how to interact with the library. None of that was provided in this course.
Feb 25, 2018
Extremely good introduction to network analysis. The course heavily relies on NetworkX, and doesn't require extensive programming knowledge - with the help of Google, you may easily solve all problems. The lectures were well structured and easy to follow. Having said this, I have found 2 major drawbacks: 1. I would really appreciate some external references so that I could get a theoretical introduction to the materials taught. 2. The last assignment required machine learning, which was not taught in this course. With the help of the forums and a bit of googling, it is easy to get full mark, but perhaps the authors could include such background in the provided notebooks?
創建者 Vinicius G•
Jan 29, 2018
The explanations were very really good and clear but not enough to complete the assignments. The assignments were over the top in difficulty. The hardest in the entire course program. That is the only reason I took one star. It was because I felt that the classes did not prepare for the assignments. Or, assignments should have a more clear explanation of the steps to be taken in order to complete them. Definitely we should look for answers ourselves but not being able to clearly understand each step throughout the assignments really limited my research area and increased my frustration.
Sep 19, 2017
Learnt considerable amount about social network from this course, as introductory level, materials (lectures and assignments) are well-prepared, much better than course 4 (text-mining). Assignments are not too hard, probably has relative good foundation from previous 4 courses. Auto-grader is a real pain in this specialization (course 3, 4 and 5), need to go through thorough test before release.
Do not consider this specialization as intermediate level.
創建者 Brandan S•
Sep 19, 2017
Pro: Required interpretation of methods presented for application on assignments without explicit direction. Required application of knowledge gained in previous specialization courses.
Con: Explanations of social network analyses were limited in number and shallow in coverage.
創建者 Robert J K•
Dec 19, 2018
The course starts off a bit slow but gets you used to the NetworkX module. The last exercise is a pretty neat culmination of the this course and specialization. It would have been cool for it to also involve text mining, but I enjoyed it and the course in general.
創建者 Carlos F P•
Feb 07, 2020
The course provides a great introduction to graph analytics, I consider that the social network applications are very sparse or missing in action altogether. Nonetheless, overall great content and practice of extracting information from networks with Python.
創建者 Jose P•
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.
創建者 Srinivas K R•
Oct 09, 2017
Good overview of network concepts using networkx - wish the course were a few weeks longer for it finishes just when you feel you can begin to something useful with the basics you have learned - but you do learn the basics.
創建者 Bernardo A•
Oct 08, 2017
Really good overview of concepts and analysis related to 'graphs'. Could be more challenging when it comes to projects: for example, teach students to gather real data from twitter or facebook and make graphs with it.
創建者 Chris M•
Oct 08, 2017
I know its hard to go in deep detail with these courses. If you used one graph and gradually built upon it through the course it may reinforce the concepts better. Thoroughly enjoyed though, learned a lot.
創建者 Chad A•
Jan 13, 2018
The material and assignments were great and well aligned. The autograder for the Jupyter Notebooks was finicky at best and resulted in lots of time wasted getting formatting correct.
創建者 Eric M•
Oct 09, 2017
This was an excellent overview of using and analyzing graphs with Python. I learned a lot, got to apply my learning from previous courses, and I earned my Specialization!
創建者 Raul M•
Jul 06, 2018
Great class for an introduction to networks.I didn't give it 5 stars because it didn't give me enough information to apply the concepts learned to real life projects.
創建者 Vishal S•
Jul 16, 2018
Lectures are very well-designed. Especially, the assignment of week 4 is too good, that give me an overview of how we can apply machine learning in network analysis.
創建者 Steffen H•
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.
創建者 Sean D•
Jun 26, 2019
Overall, good course. It could use more explicit examples of NetworkX in the actual Jupyter Notebook itself, but the coverage of the material is high quality.
創建者 Yuzi H•
Jun 28, 2018
The presentation documents are very helpful to understand the lectures. If they can be downloaded to our local laptop, I evaluate this course 5 stars.
創建者 Alejandro B•
Jan 11, 2020
Great course, however, there is quite complicated the autograder system. Sometimes it takes too much time trying to figure out technical issues.