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.
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.
автор: Raul M•
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.
автор: Vishal S•
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.
автор: Steffen H•
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.
автор: Sean D•
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.
автор: Ezequiel P•
Great course! The topic is very interesting! I would have liked it to have more hands-on approach during the lectures, but the course quality is great
автор: YUJI H•
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.
автор: Alejandro B•
Great course, however, there is quite complicated the autograder system. Sometimes it takes too much time trying to figure out technical issues.
автор: Martin U•
This was a great course, lots of great insights to gain. Only thing that was frustrating was the multiple choice quiz questions. I hated those.
автор: Tom M•
A bit confusing material since it is new to me. Lots of material in a short course. The auto grader is a bit difficult to work with.
The course provides a good overview of basic measures for network data. I took as prep for a harder course. I would recommend it.
автор: Dmitry B•
This course was easier that the previous 4 in the specialization as it used them as a foundation for practical graph analysis.
автор: Victor G•
Intreesting and rich in learning. The last assignment was specially fun. Would be nice with more such free assignments.
автор: Daniel D A•
I liked the lectures but the assignments were significantly harder and had content that we didn't learn in the lecture
автор: Lucas G•
Nice overview of general graph theory, and some useful exercises on how it can be applied for social network analysis.
автор: Mike W•
If you've had prior expose to graphs (e.g., an intermediate-level CS course), the first 2.5 weeks is pretty easy.
автор: Shashi T•
This was wonderful course in terms of content and content delivery. Prof was really nice. His pace was very good.
автор: Bart C•
Great course! Love the instructor. Good background in networks, while sticking to the applied side of things.
автор: Juan V P•
Good course with a nice and clean talk professor. Perhaps I miss some real-world cases in the assignments.
автор: Gregory C•
Pretty well designed course, except that I found myself battling the auto-grader too often.
автор: Mohit M K•
One of the more tougher courses in Social Networks but still would recommend to everyone!
автор: Anad K•
Good Content! And the assignments were just right to augment effective learning.
автор: Juan M•
The machine learning connection could have been mentioned earlier in the course
автор: Minshen C•
it would be great if some case study of prediction can be added to the course
автор: Jonas N•
Highly valuable course and a good starter for network analysis. Do recommend!
автор: Divyansh R•
Great instructor. Very engaging videos and thought-provoking assignments.