Ratings and Reviews for Applied Social Network Analysis in Python

Daniel Romero is probably the best instructor in this specialization

Great course

My favourite course

Amazing course!!!

Great Content!!

One of the best courses on social network analysis. Professor Daniel Romero did an excellent job explaining the contents.

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.

The machine learning connection could have been mentioned earlier in the course

Very helpful, I didn't know anything about graphs, networks modelling and the NetworkX package before this course.

i found this course to be fun and straightforward. The assignments were directly aligned to instruction. Great course!