NC
7 июля 2020 г.
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
PP
13 нояб. 2018 г.
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
автор: Samuel S
•4 нояб. 2017 г.
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.
автор: Vincent R
•2 окт. 2018 г.
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.
автор: Muhammet T
•8 мар. 2021 г.
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
автор: Simon B C
•12 апр. 2020 г.
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.
автор: Gabriel T
•22 мар. 2018 г.
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
автор: Samuel C
•30 дек. 2017 г.
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.
автор: Ricardo L C T
•18 окт. 2017 г.
the chat part (graphs) was hard to finish. the bar is very high for this capstone. anyway very good course.
автор: ISLAM K
•22 мар. 2019 г.
its very good course , here its aggregating all knowledge and information learned in previous courses
автор: Allyson D d L
•26 апр. 2022 г.
This course was good to provide more practical lessons using Splunk, KNIME, Spark MLlib, and Neo4j.
автор: Jeffrey K
•7 янв. 2021 г.
A lot more work and time than expected. Some issues with software tools as per expected.
автор: Sascha Z
•7 авг. 2017 г.
Watch out for week 4. This is the hardest one out of the whole specialization
автор: Mark d B
•18 июля 2017 г.
Very good practice with the things leart in the other 5 courses.
автор: Santiago A G
•7 сент. 2018 г.
Good and very practical challenge
автор: moataz
•7 окт. 2020 г.
Good Job, thanks for all
автор: To P H
•23 февр. 2019 г.
Not Bad
автор: Hien B L
•11 февр. 2021 г.
GOOG
автор: Mohan R S
•3 июля 2020 г.
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.
автор: William S
•9 июля 2020 г.
Poor instructions that need to be revised and updated. Nice to exercise the skills and tools you learned in the prior courses.
автор: Miguel T
•31 дек. 2018 г.
The course is really good, but some exercises are difficult to be done without technical support.
автор: Pradhyumn A
•15 сент. 2020 г.
should have been more indulging else fabulous
автор: William R
•26 нояб. 2016 г.
The capstone, just like the courses of the specialization are a strong illustration of the problems of higher ed.
автор: Mario L
•26 июня 2020 г.
The tools user in this course have too many bugs and a lot of time is lost on it.
автор: Ahmed N
•24 мая 2020 г.
one of the worst courses I have ever had on coursera