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Вернуться к Big Data Integration and Processing

Отзывы учащихся о курсе Big Data Integration and Processing от партнера Калифорнийский университет в Сан-Диего

4.4
звезд
Оценки: 2,370

О курсе

At the end of the course, you will be able to: *Retrieve data from example database and big data management systems *Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications *Identify when a big data problem needs data integration *Execute simple big data integration and processing on Hadoop and Spark platforms This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+....

Лучшие рецензии

SB

21 окт. 2020 г.

Hello Gentlemen,

This course was very helpful foe me. It enhanced my knowledge about Big Data Integration. Thank you so much for providing me such important knowledge. Thank you once again.

AA

5 мар. 2018 г.

It was a good course, it could have been better if some examples of Spark were also provided in other Languages like Java, people without having background of python may find it difficult.

Фильтр по:

401–425 из 503 отзывов о курсе Big Data Integration and Processing

автор: Leonardo L

10 авг. 2020 г.

the instructions to the final test are insufficient and the forums cant fullfill the students questions.

автор: Venkateswara P S

2 сент. 2020 г.

One of the tools mentioned tin the course do not work with Cloudera any more. So my labs became tough.

автор: Tatiana M

28 февр. 2017 г.

A little slower than the last ones, not my favorite but great use of hands-on projects and enagagement

автор: SU C G

23 окт. 2016 г.

Needs more depth. Instructors should reference more external readings since the lectures are brief.

автор: Anirudh

25 дек. 2016 г.

some of the stuff was not mentioned properly, like for last quiz how to expoert data from mongodb

автор: Pablo A L Z

28 июля 2020 г.

THERE ARE MANY PROBLEMS WITH ANACONDA INSTALLATION AND PYSPARK NOT RUNING CORRECTLY

автор: Nester P

10 сент. 2017 г.

The last assignment of Week 6 was far more advanced than the rest of the material.

автор: Luis O

27 апр. 2020 г.

You could focus more on Spark that is the widely software for Big data Processing

автор: Erik P

14 окт. 2017 г.

very nice, just wish the environment was using docker instead of virtual machines

автор: Silvia C R S

28 окт. 2017 г.

I think that there should be more exercises for MongoDB and Spark assigments.

автор: Ramathmika

2 апр. 2020 г.

Not very efficient hands-on practices but overall good learning experience

автор: Dev A S

19 янв. 2020 г.

Good course. But we couldn't relate the theoretical videos with hands-on.

автор: Vish V

18 сент. 2021 г.

Teaching is good but practice software provided completely outdated.

автор: Vadim C

5 нояб. 2016 г.

The final assessment somewhat not really well designed, imho.

автор: Oleh D

11 нояб. 2020 г.

Pyspark environment is quite not ready for this course.

автор: Ashish J

24 авг. 2017 г.

spark hands on should have been more instructive.

автор: Manas D

9 авг. 2020 г.

mam teaches well while sir is not good at all

автор: JAMES F

5 авг. 2019 г.

Good info, just a lot of info to digest.

автор: Konstantin K

1 мар. 2018 г.

All is good except the Splunk case

автор: Ho S J

21 июня 2017 г.

Very difficult final exam.

автор: Soham B

17 нояб. 2022 г.

Course needs update

автор: Brajesh L S

27 апр. 2020 г.

Tough one.

автор: Keith B

31 мар. 2017 г.

The course and presentations were very informational and good. I enjoyed that aspect. I would have rated the course 4-5 star based on that. The reason for the low rating was the 6th module, and the fact that I felt very ill prepared for the syntax of creating all the operations in Spark (building out the Jupiter notebook). We really did not cover much of that, and it was quite punishing to search the web and sources to make things work. Even the instructions to export the csv file were misleading at best. I have a full time job and a family, I am not some young undergraduate with copious amounts of time to waste. While I am not opposed to some searching of other sources, I would like to have more of the useful information taught so that it is not so much of a burden. I believe that if you are going to test people on something, you should at least cover it in some sense.

автор: Markus S

3 мар. 2019 г.

With deep regrets I feel obliged to share a negative rating on the course. While the course material/video lectures are average to good (no rocket science but well done introduction into the subjects), the hands-on exercises and particularly the technical environment, i.e. Cloudera VM is entirely messed-up: - setup scripts are not working/ are outdated (e.g., anaconda requires no-check-certificate); user permissions are all set wrong and need to be corrected; firefox outdated with update function not working; countless error around spark context (SC) variables.... and so on... For a course that is so prominently promoted on the platform the least expectation is that the provided environment works and that students don´t need to spend hours on google to figure out how to debug the cloudera image.... Here, imo, a much better job can be done!

автор: CJ F

12 апр. 2022 г.

This course is not maintained, so you have to spend many, many hours finding out how to do the coursework. This really is unacceptable. Please look for alternative courses to this one. This is the same as all the courses in this specialisation. A real shame, as I've said in previous reviews for previous modules.

That said, the theoretical observations are timeless, so if you can use the course for that then that is good. And the soccer tweets analysis at the end was quite interesting - although it took me so long to actually be able to do the exercise that it ended up being really frustrating. This course would be amazing if they ever updated but it looks like they never will - the discussion boards are like a graveyard and there is no real peer-to-peer interaction that I can see.