I encountered numerous issues with the hands on exercises. Either copy paste errors or the VM simply hanging.

Pros: good explanations, examples and hands on modules.

Cons: Out of date content in the last module.

The last two weeks was very hard to understand. This module could be a separated course.

A lot of unanswered doubts. And a lot of improperly explained concepts and codes.

The course is good, but I would prefer the examples to be coded in Python.

not much explanation about the syntax of the commands given in excercises

All the complexity of the course is concentrated to the last week.

Great material. Too many technical issues. Possibly outdated.

It's necessary to update the documentations of the course

Need to include more student project design in the course

i would have prefered more analytics and less tools.

should update the course materials and the tutorials

Too much time spent on tools installation

was not able to load the files in neo4j

Helpful reviews are very reasonable

Week 5 seemed irrelevant

My problem with this course is the same that with the Machine learning course: it is too basic, and the big data aspects were more a demo than a real course. I know about graph theory and networks in general much more than it was covered in this course, and I was disappointed that all the big-data context was limited to the handson sessions of week 5. I have to mention that the theoretical parts (first 3 weeks) were high quality and nice, just did not cover anything new for me.

On the contrary, the graphx handsons were drafty and really lacked explanations of the steps. I suggest to rename this course to something like "Introduction to graph and network analysis with a big-data demo" not to mislead users.

There were a number of software configuration settings for which we were not forewarned, some settings that I saw now way of changing in the community edition of Neo4j, and the queries in week 5 were not adequately explained. Furthermore, some of the earlier lectures appeared to be "modified from the original lecture, cut down to create required material and optional material. The lectures were cut in crude fashion, and the instructor would go from one slide to the next, sometimes starting in mid sentence. This subject can be interesting and useful information, but the content needs to be reworked so that we better understand the software use, and what we are trying to achieve.

My personal opinion but we seem to be just breezing through at a very fast pace the details associated with the applications. We are presenting but not really conveying anything meaningful given the pace that they are covered. Seems more of a distraction than value to the overall objective of the course. It would make more sense just to provide a slower placed recorded session on the tools .. and I do mean slower with explanation. Perhaps and optional course where there could be a deeper drill down into to the apps. It also seems that some of the course material is not up to date with the current versions of the apps as well.

While there is very good content in this course, just like the others in the Big Data Specialization the material is out of date with the tools, there is not enough guidance on the use of the tools, and no one curates the material to keep the directions for using the tools current with the tools. This makes these courses hugely frustrating and a huge time suck without providing insight or value other than how to search the web for answers to fixing all the screw ups in the material.

Over All this makes the course extremely POOR

This course continues the style of the specilization. Wrong instructions, theoretical lecture and inconsiderate course structure. Maybe this course includes too much concepts and skills and students may not be able to command all of them within such a short period of time. I have to say it's a waste of time to download all these softwares in the course.

All kinds of issues with the hands-on assignment software. Sooooooo much time wasted trying to get things running and/ or files loaded etc. This course + specialization MUST be completely overhauled because all of the chosen software models/platforms are much updated themselves, otherwise, just take it down from Coursera altogether!!!

First week of 3 min video. Seriously we want to dive into the subject. And the last two weeks should have more content. Felt like much more copy and paste without understanding why you did that. Understand this should be introduction to Big Data... But the price you pay for the introduction is too expensive.

Full of errors, short of explanations and support, just trying to figure out what to introduce in the command line, not knowing what I am actually doing and why. There are issues reported in the forums eight months ago that have not been fixed. At least one can get a fair idea of what can be done.

Some items are interesting, but the lectures seem goal-less: not enough structure to help understand graph analytics. There's something there but I didn't have much of a takeaway. Introductory material should have more structure.