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返回到 Serverless Data Analysis with Google BigQuery and Cloud Dataflow

学生对 Google 云端平台 提供的 Serverless Data Analysis with Google BigQuery and Cloud Dataflow 的评价和反馈

3,121 个评分
312 个审阅


This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • Google services are currently unavailable in China....



Dec 12, 2018

The combination of Java and python is sometimes a bit confusing. Maybe it would be better to split the course in a java and a python version so all the Beam concepts are taught in a single language.


Jul 21, 2019

Thanks for designing such a wonderful course outline. I learned valuabe BigQuery and Cloud Dataflow concepts. Best part was to learn how to write data pipelines and execute on cloud using Dataflow.


276 - Serverless Data Analysis with Google BigQuery and Cloud Dataflow 的 300 个评论(共 310 个)

创建者 Eugine K

Aug 20, 2017

Labs were not detail enough.

Wish to see more examples of different transforms available in Beam

创建者 Amilcar B

Sep 03, 2017

Two of the labs did not work. But still a valuable course.

创建者 Parth J

Oct 28, 2018

I am not good with Java and Python and this training was more around them and not to Data flow. I do not know but may be we can do some simple examples to use data flow.

创建者 Chris H

Oct 31, 2018

Why is there only sound for half the videos? This is not the only course this is happening to.. fix this ASAP

创建者 Michael W

Jul 24, 2018

Started out very solid and then it just fell a bit short on some of the key exercises. Probably should have started with the Data Prep Tool & Templates before heading into Beam pipelines and Side Inputs and those two could have been more detailed. I finished this course in 1.5 days so you had a bit of room to make it more robust with a week being the expectation.

创建者 Rushi P

Jul 29, 2018

BQ portion, very helpful.

创建者 Asim K

Jul 16, 2019


创建者 Martin W

Aug 05, 2019

Check progress in Quicklabs does not provide useful help. Some quicklabs are hard to complete, if you made once something slightly different and it was not recognized as a result.

创建者 Indrek V

Aug 26, 2019

Multiple technical errors on this course. One lab had to be completed multiple times because of progress check errors. Course progress updates seemed to be "rolled back" at one point. Last quiz in the course simply won't load. Maybe Coursera and Qwliklabs are just having a bad week...

创建者 Subhrendu B

Jul 10, 2019


创建者 Jacopo O

Nov 26, 2019

not updated for python 2

创建者 Michael B

Apr 25, 2018

Similar to the others, a lot of waffle and only the very basics taught.

There's also duplication of questions across quizzes which are incredibly easy

创建者 Lucas d S R

Apr 26, 2018

For an intermediate course the demos are too simple. The concepts presented are clear but there's very little depth on what's covered. It is, at best, an introduction to Dataflow/BigQuery rather than a complete course.

创建者 Jim B

Mar 25, 2018

Unpolished. Little depth. Labs ran really slow. I can't believe this was $99.

Instructions for labs were the bare minimum and only after the video reviewing the lab (which seemed like padding for time to me), did you understand the lab,

Why not have java AND python videos -- switching back and forth was annoying.

创建者 Nathaniel B

Jul 06, 2018

It's good to learn about BigQuery, Dataflow, and Dataprep. The training should include more than tutorials. It should include recreation/emulation and generation on the part of the student. The reviews are infrequent and not very useful for highlighting the most important information. A couple of the labs do have good questions that ask the student to explain code or predict it's output, but it can be better organized so that the student can get immediate feedback on whether he/she is correct. Dataprep seemed like an afterthought in this course and lacked an opportunity for the student to explore it in a lab.

创建者 Jeronimo G

Jul 27, 2017

I'd expected a more deep course

创建者 Justin

Jul 27, 2018

Really verbose. Also the labs kinda sucked.

创建者 Gonzalo A M

Aug 02, 2019

a little confusing how to work with dataflow and the process is too long!

创建者 Juan P

Nov 17, 2019

Really disappointed with this course for the following reasons:

1.- Out of date as the screens shows in the videos no longer match reality

2.- Broken labs for Python. Need to spend time debugging the class code to actually make it through

3.- Video where the screen is still in the first slide, but the speaker is clearly describing slides that we cannot see

4. A few of the class slides that have way too much information in them. The speaker is desperately trying to explain what is going on those slides (not very well).

All and all, this is my third Google class in Coursera and it is clearly lower quality that the other two.

创建者 Diego T

Nov 22, 2019

The labs have a problems.

创建者 Yitao Z

Nov 28, 2019

Generally it is boring and lacking stress on main objectives. No matter in functional characteristic or in programming aspect, the course is vague and intangible.

So many narrators showed up in the vedio and some demo interface is totally different with nowadays(e.g bigquery edit panel). This made me doubted about bigquery's stretegy position in GCP product line.

Please re-capture the vedio with well prepare narration.

创建者 Sim K Y

Jan 31, 2019

Lab system is EXTREMELY slow.

创建者 yan c

Sep 09, 2018

Some labs are not even been tested at all. No git repo, the instruction is incorrect. Environment is not set up correctly.

创建者 Aaron C

Sep 10, 2018

passive learning = shit learning

创建者 Yoong S C

Sep 24, 2018

Really mediocre.