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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: 2,341
Рецензии: 507

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,\n\nThis 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.

FC

24 сент. 2016 г.

Best course taking into account the first three. Good material, more in depth than the other ones. Very well explained. Useful to get a sense of various interesting topics and orientative.

Фильтр по:

401–425 из 496 отзывов о курсе Big Data Integration and 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: Mouâd B

6 дек. 2021 г.

U​nmaintained resources.

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.

автор: Silvain d M

23 авг. 2017 г.

Although the contents of the course is good, I found that the hands-on exercises needed to pass tests were problematic due to many errors occurring when trying to setup the tools or running provided scripts. This means most of the limited time I have for this was spend browsing the course forums and the internet chasing solutions for errors occurring in the exercises and not on actually working on the assignments.

Also the course makes you install several tools/apps. In itself it is good to be exposed to these tools, however some of these are only used to a limited extent, while still taking time to install and setup. Worst is one of the tools requiring personal information in order to be downloaded and as a consequence being chased by sales reps for the tool.

автор: Christoph S

3 апр. 2020 г.

Again I'm torn between quitting this specialization and biting through the rest of it. While the course is good on the high-level view, the link to the low level, the tools and their application just doesn't work well for me. The different tools are presented and used just enough to scrape a tiny lttle bit of the surface, then you're heading on the next chapter. Like in the previous courses, the tools in the VM sometimes need quite a bit on tinkering until everything works as expected. The main drawdown in this course was the final test that I did not felt prepared for at all. On the bright side, you learn to love the Spark manual...

PLEASE, UPDATE THIS COURSE AND BRING IT TO TODAYS LEVEL. IT'S ACTUALLY BETTER THAN THE AVERAGE FEELING IT LEAVES BEHIND.

автор: Vincent O

18 янв. 2021 г.

Course materials are dense in high-level knowledge whereas the final project is technical. The hands-on learning is too linear and hand-wavy to leave users a programming assignment at the end of the course without the same constraints. The course was great in general for the subjects it covers. I do not think the applied hands-on learning is done in a way that gives any lasting understanding. I've given only two stars mostly for the reason that it took over 2 hours of my time simply debugging issues with the included VM to allow me to complete any course work. I would not expect that someone without a systems background would be able to complete the course work at all because of the several core issues with the VM configuration and included packages.

автор: Andrew D

14 окт. 2016 г.

Overall this course does have some good content and delivers big data concepts. However, as others have mentioned some content (especially in early modules) could either be combined or ommited. Key focus areas on Spark and MongoDB are not given enough focus and lab time.

The quizes have badly worded questions. Finally the last assignment required to pass the class has bad directions and covers content not reviewed in the class. Spent a frustrating amount of time trying to get what most likely is simple code to work.

I'm hoping this particular module is revised. For those just interested in learning Spark or Mongo and not doing the certificate program you can probably get better learning from doing your own research.

автор: John F

10 авг. 2020 г.

I'm about halfway through this course and the specialization as a whole.

It it apparent that these courses were created a few years ago and have been left to their own devices since then. Any software version that you need to download is so old it may not even exist, and if you want help with it don't count on any responses.

Also as this specialization goes on, it seems to be more and more abstract, wordy lectures where you will absorb very little, and then a rushed assignment where you try to apply something literally one time before they move on to the next item.

With this level of engagement and assignments I will end up having to actually learn this stuff elsewhere from someone who knows how to teach.

автор: Joaquim P

14 мая 2019 г.

I think that this course doesn't provide a substantial value to the student. It's basically a series of theoretical videos with irrelevant exercices that the student doesn't even have to think about. It's only about copy and paste until the last assignment. Until then, it's just a waste of time. Obviously it will be a good course for those people who only want the certificate and to pass the course with no effort at all, but it provides no value. On top of this, there is no technical support and I have struggled a lot in order to make everything work properly. I also suggest Coursera to give some guidance in the last assignment, there is a lot of lost people.

автор: Ryan H

12 июня 2017 г.

Again, another course in this series shows a lack of effort in its quiz construction. By the final week, you are presented with a challenge that will require numerous hours pouring over different documentations of both pyspark and MongoDB because there is a lack of essential knowledge being taught in the course. The final "project" is based on a very small amount of what was learned, and as it so happens, only a small amount of what was needed was actually taught. I'm hoping for improvement with the rest of the course, because the majority of this course was good, but the final week just ruined the experience.

автор: Guillem P

10 янв. 2017 г.

The last assignment of the course is, compared to the others, more difficult. In my case, I ran into several errors which I couldn't get help in solving by using the course Forum, as the end of course deadline was just a few days ahead. I had to analyze the tweet texts for the last graded assignment without using Spark framework (nor any of the other "Big Data" tools explored in the course).

I also found some of the videos by PhD. Amarnath Gupta were difficult to understand, his examples were unclear and, in my opinion, too complex and difficult to follow and understand what was the reasoning thread.