Ratings and Reviews for Applied Social Network Analysis in Python

All the assignment have issues,.

well structured and provides the foundations for network analysis - connecting it with real-world use cases.

Did not make clear the prerequisite requirement to understand machine learning classifiers using sklearn library. Had to go back and teach this to myself in a week in order to complete finial assignment. This should be in the prerequisites for the class.

really interesting introductory course.. originally took it just for credit transfer, but ended up being interested in the topic. I'm from engineering background, though not computing. Some coding did take me some time to finish. Nice degree of challenge to stretch me. Overall glad that I took this course. Got to know that social network is not only used in social network, but can also be used to analyze flight & airport network, optimize search engine etc.

Nice Course. Some topics are quite hard but understandable.

The professor was great! The way he explained everything was clear and understandable. The mentor, Uwe, in the course was also super helpful when other students or I needed assistance during assignments. The only reason why I gave this course 4 stars rather than a 5 was that there were many errors in the assignments and auto grader.

Good course. Covers both concepts and practical aspects.

Helpful course with rich material for my learning

Good introductory course for conceptual understanding of Network Analysis in Python. Good assignments, would be great to have more real world examples and hands-on business case studies for application of Network Analysis in different Industries. Also, they should update the course to use recent version of Networkx - 2.8 library.

Great!