hand on is quite hard and need a lot of installation such as cloudera.

Very good project! Hopefully it will be helpful in my future career!

Suggest to remove the peer-grade assessment as it could be bias :)

Can be improved further by including rigorous Hands-on exercises

Within the usual pedagogical standards, it is a very good course

I really enjoyed learning graph analytics, great course!

It's really long and we need more practical examples

Things made a bit too complicated sometimes.

Week 5 materials are not well prepared.

This is a great introductory course.

Thanks so much

you are great people

interesting practices with neo4j

Nice overview to get into it.

best course of the series

well explained

buen curso

Not bad

Thanks

Good!

-

The course theory was illustrated and demonstrated very well. Examples were shown and the lectures were short but concise. I appreciated this greatly. The professor also spoke very slowly and deliberately, so the viewers could understand and have time to let the information sink in. In contrast, although the guest lecturer for Neo4j was great, the material was not up-to-date and caused several issues in completing the assignment. Other students were able to lead the class in the right direction in order to even start the assignment. The GraphX on Cloudera virtual machine was almost impossible to replicate as well due to the material being so outdated. Week 5 of the course peaked my interest but lacked the resources to completely follow the instructions and understand the material that was being presented.

I would have liked to put 5 stars. This topic is so important and relevant to big data. After week 4 hands on part, it became obvious we will not see how to implement or interpret the more abstract graph concepts presented in week 3. That was very disappointing.

Moreover, the structure of the course is not as good as the other module. I don't understand the lack of balance between theory and hands on (Not enough hands on to reflect the theory) part.

On a constructive note, I would replace some of the theoretical concepts of week 3 with additional information on how to link a graph database to machine learning OR I would add more hands on exercise to help using those more complex concepts and learn how to interpret them.

The professor is well spoken and the class started out very well. But by the final section the hands on example were simply cut-paste with no explanation of what we were doing or how it worked. It's not the fault of the professor but this course and the Big Data specialization attempts to cover too much information. Graph Analytics should be its own 6 course specialization. But really, to understand graph analytics one should be spending a great deal of time with the subject. Perhaps online courses are not the way to understand such a complex subject.

Unfortunately the videos and lectures about Neo4j installation is not up to date making it difficult to install by the learner. Mostly if you take into account that not all the students have the technical background to do it. On the other hand, after installation Neo4j was returning an error that don't let complete the labs. Regardless these issues, all the other course content is really helpful to get a high level understanding of how Graph Analytics can be used in a Big Data ecosystem.

Probably because I'm new to all the big data and graph analytics terminologies but the lectures in this chapter were quite difficult to follow in my opinion. The instructor was just talking, not teaching nor explaining, just like someone who prepares notes and is reading to students. The hand-ons were a bit helpful, but overall this class is more for those who already know about the subject.