The course was great for the most part. The material was more challenging than previous courses in the specialization and really helped me pull everything together and understand everything a bit better. I will say that I felt there was a huge gap between what was taught in the Neo4j course and the Neo4j assignment in the Capstone. I'd learned a lot from the assignment, but it took me loads of time and their were parts I still don't really understand. There are also a some broken hyperlinks to previous course material. I'd also like to see better support for a paid service. There is no interaction from a Coursera employee or course instructor in the forums at all. It would be nice to have someone to clarify some instruction or material that may not be clear at times.

Great course that uses a project to apply what you learned in the others courses. I enjoyed it a lot.

The only point is the technical issues in the installation, compatibility of the cloudera version and softwares to be updated. It is necessary to give more support to the technical issues detected, else as a learner, you spend a lot of your time solving them.

Anyway, I definitely recommend this course if you want to keep learning a lot, It's worth the effort!

Interesting final project to complete this course, didn't get 5 stars because:

Clarity could be improved in the instructions and solutions of the assignment

However this is counter-balanced by the amount of plagiarism (if you provide more detailed solutions, some people unfortunately will just copy/paste them).

So I am still wondering how the final results in week 4 were obtained....

Some of the instructions for the tools are not clear enough. It's better to have some more suggested further readings - like statistics with KNIME, operating Spark, etc. For the cases, it is very straight forward and with beautiful data; likely far away from real application.

The Big Data - Capstone Project is a great course that is very challenging and requires a significant amount of work hours for a big data first-timer. The great experience could be enhanced by fixing some bugs in software and typos in guidance document.

I liked the content and presentation of the courses. However I had experienced problems with the Virtual Machines and had to tussle around to solve some exercises, using some cloud based options of the tools

Overall a good capstone project. However, the guidance is inconsistent some times. Also the setup for PySpark is not working for a lot of students, for at least 3 years, and they did not uptdate it.

Very engaging course. Well designed and delivered. I also liked the breadth and depth of the course. Liked it and continue use the material as reference

The project is really helpful to sum up the whole process of the 5 previous courses, but there is a bit problem with the week 4 assignment.

the chat part (graphs) was hard to finish. the bar is very high for this capstone. anyway very good course.

its very good course , here its aggregating all knowledge and information learned in previous courses

A lot more work and time than expected. Some issues with software tools as per expected.

Watch out for week 4. This is the hardest one out of the whole specialization

Very good practice with the things leart in the other 5 courses.

Good and very practical challenge

Good Job, thanks for all

Very helpful course

Not Bad

GOOG

It seemed the assessments were a little difficult, although I did enjoy it pu. I saw lots of learners copying each others content. We need to try stop it.

Poor instructions that need to be revised and updated. Nice to exercise the skills and tools you learned in the prior courses.

The course is really good, but some exercises are difficult to be done without technical support.

should have been more indulging else fabulous

The capstone, just like the courses of the specialization are a strong illustration of the problems of higher ed.