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...
Ratings and Reviews for Applied Social Network Analysis in Python
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Reviews and Ratings
Reviews
in my opinon, the best of the specialization. thank you
Excellent course and professor!
Remarkably good explanations, and interesting selection of subtopics. Interestingly , it does not delve into Facebook or any other social media applications, and is still just as valuable as it covers Graphs in some depth. Uses Python and its NetworkX library. Knowledge of classification models and scikit-learn is needed for the 4th assignment.
Highly valuable course and a good starter for network analysis. Do recommend!
Awesome. Worth it!
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.
Coming into this course, I didn't expect much but I was pleasantly surprised by the quality of the material. The quizzes were especially designed well and the final assignment was really challenging and instructive. I wish there was more of predictive modeling using network features but the rest of the course easily makes up for that.
Excellent course.
Very interesting topic and well-made lessons.
