Chevron Left
Вернуться к Big Data - Capstone Project

Отзывы учащихся о курсе Big Data - Capstone Project от партнера Калифорнийский университет в Сан-Диего

Оценки: 388

О курсе

Welcome to the Capstone Project for Big Data! In this culminating project, you will build a big data ecosystem using tools and methods form the earlier courses in this specialization. You will analyze a data set simulating big data generated from a large number of users who are playing our imaginary game "Catch the Pink Flamingo". During the five week Capstone Project, you will walk through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting. In the first two weeks, we will introduce you to the data set and guide you through some exploratory analysis using tools such as Splunk and Open Office. Then we will move into more challenging big data problems requiring the more advanced tools you have learned including KNIME, Spark's MLLib and Gephi. Finally, during the fifth and final week, we will show you how to bring it all together to create engaging and compelling reports and slide presentations. As a result of our collaboration with Splunk, a software company focus on analyzing machine-generated big data, learners with the top projects will be eligible to present to Splunk and meet Splunk recruiters and engineering leadership....

Лучшие рецензии


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


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

Фильтр по:

76–99 из 99 отзывов о курсе Big Data - Capstone Project

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.


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