Really disappointed with the Virtual Machine related exercises throughout the whole course, not only the capstone, where literally I have spent more time trying to figure out how to make it work and do not get any error message than actually learning big data. Very very frustrating.For sure not going to recommend this course to any friend.

This course deserves no starts. There were no instructors answering the many questions raised by the students. There were no explanations for wrong answers, and so no opportunity to learn. I was helping other students understand the assignments, and spent extra time grading submissions as no teaching assistants were available to help.

There were a couple of very good teachers in the specialization, however the structure is critically flawed and your time would be better spent studying on your own.

Avoid not just the capstone, but this entire series.

The exercise with the graph is way outside the difficulty level reached in the course. Either provide futher detailed steps to complete with more in-depth explanation of the neo4j query language or simplify the exercise.

Unnecessarily prevented me from completing the specialization when I had time to make me pay extra. I had to wait 2 months for the capstone project to start, enough time to make me forget how I dealt with the excessive number of problems in this outdated course.

Trivial assignments. Low quality lectures. Wrong, conflicting and obsolete instructions. Discussion forums are barely moderated and are filled with spam.

Working with Splunk is impossible. Taking this course, my intention was not to learn SPLUNK!!! My intention was to perform an intensive, deep and meaningful EDA. However, I've spent 2 days (!!!) for learning...Splunk which is a complex tool of extremely poor usability. This is why I prefer to quit the course and the project (which I really wanted to participate in.

OMG!

This is the best specialization of my life.

I really enjoyed the dozens of skills in this specialization.

I have no more words to express my feelings.

Courses 1,4,5 & 6 are wonderful.

"Machine Learning with Big Data", "Graph Analytics with Big Data" and Capstone courses are mind-blowing.

I have no words to express my feelings. I can say many thanks to the instructors Ilkay Altintas, Amarnath Gupta and Mai Nguyen for delivering such amazing content.

Big Cheers for Coursera.

Very simple but a very informative specialization. This is an excellent introduction, you will need to study some topics like machine learning further to get a better understanding. If this was to be extended to a 10 course Specialization I would love to see more on model selection, model interpretation, regression and regularized regression, error analysis and inferential statistics, model assembling and free text analysis.

Excellent course for introduction to Big Data. This course covers some of current software that is used in big data processing such as Splunk, Knime, Spark and Neo4j. The course curriculum is designed to help you learn the materials and complete the certification successfully. Great job Professors Ilkay Altintas, Amarnath Gupta, Mai Nguyen. Thank You.

Kevin Murali

In general the course is very good. There is a lack of support, especially when some exercises are proposed and then the final solution to the problem is not available, which requires a lot of search for solutions on the web. Even so, at the end of the course it is possible to get a good knowledge about the complete big data process.

This is very helpful project where i have applied all learning through ouot journey of this course.Though it was time consuming but worth to invest time, which benefits to upskill my knowledge

Good project, but needs a big overhaul as many instructions just don't work right out of the box due to recent software updates and it was more difficult to make all the exercise tools work than doing the actual exercises.

This is all you can expect from an online course, imho:

all the stuff you learned in the courses belonging to the Big Data specialization coming together in hands-on exercises, that not only test your knowledge but also are fun to do and give you a real taste of a Data Scientists work.

In the beginning, it´s a bit overwhelming, how many new technologies and programming languages you are introduced to and have to exercise, but it is definitely worth it. And the course material is well designed, that you do not get lost. You get a lot of help in the instructions, that even beginners should be able to succeed. But there is also enough room to explore and try out the matter on your own.

Like they said: happy learning! Thanks alot Ilkay, Amarnath, Mai, the guy from the hands on instruction videos and all the others who contributed, affiliates.. Eğlence! :)

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11).

I did this course to complete my CV in Big Data and better understand the technology.

The course was excellent and the classes well taught by teachers.

Thank you for the support, course quality and great classes.

Regards.

Jose Antonio.

Try to fix all errors in this Capstone Project. After many weeks perfectly organized and written, this last weeks we have found too many mistakes. So try to fix them, please. Despite this, I am very proud of your and my work with the whole especialization. Congratulations !!!!!

I would like to thank all the great teachers who provided us this rich learning experience. It was very interesting to learn so much from this specialization. The hands-on are well built to allow understanding of the concepts and the tools.

Congratulations for the course preparation and thank you all. It was a very exciting investiment I have performed and I have also learned how to think differently on problem analysis after taking this course.

Really interesting insights into the general overview of the big data specialization with brain-teasing hands-on exercises and a look to hoe reporting various big data analytics should be undertaken

What a challenge, I came into this course as a London Black Cab Taxi Driver, I thought the knowledge was hard but this capstone was a challenge more intense than the Knowledge of London!!!

Good exercise to cover the whole essence of many weeks of other courses of the Big Data Specialization.

All in all, I liked the course and learned a lot, however, I am dissapointed at the grading process. Even where i was totally wrong I was given full points which for me devalues the experience quite a bit.

The peer grading needs an overhaul and people should be punished for overly good Feedback.

Very limited opportunities for support; there's no teacher to help instruct, and you are on your own for installing the software. The Graph Theory course dives into challenging content without a solid base to finish up the graph theory part of the capstone.

Well the first five courses went pretty smooth. However, when I got to the capstone project, it became a desperate case. I could finish week1 but week2-6 were locked. And it won't be open for a whole month. Apparently I was not the only person who has this issue. People complained about this issue over three months ago but no solution was offered. Of course there is no phone number, and the mysterious live chat option was nowhere to be found. I end up cancel the subscription.

Capstone is the hallmark of this Big Data Specialization course. It helped me leverage all my learning and apply it to data-driven analytics problems. The coverage included Hadoop, PySpark, KNIME, Splunk, and Neo4j to inform my understanding of the problem at hand. Project based approach also honed my problem breakdown, recommendation reporting and presentation skills.

I recommend this to all data and analytics practitioners !!

Brilliant assignment. The SPARK one was tough. At end, all the effort would make a lot of sense on how problems could be approached. Give perspective of how various tools should be used to solve data science problems

This has been excellent Learning experience.Instructor and fellow members shared their valuable information during the course of the Learning and Capstone Project phase.