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Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform に戻る

Google Cloud による Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform の受講者のレビューおよびフィードバック

4.6
3,990件の評価
471件のレビュー

コースについて

This 1-week, accelerated course builds upon previous courses in the Data Engineering on Google Cloud Platform specialization. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to create and manage computing clusters to run Hadoop, Spark, Pig and/or Hive jobs on Google Cloud Platform. You will also learn how to access various cloud storage options from their compute clusters and integrate Google’s machine learning capabilities into their analytics programs. In the hands-on labs, you will create and manage Dataproc Clusters using the Web Console and the CLI, and use cluster to run Spark and Pig jobs. You will then create iPython notebooks that integrate with BigQuery and storage and utilize Spark. Finally, you integrate the machine learning APIs into your data analysis. Pre-requisites • Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Python...

人気のレビュー

RC

Nov 19, 2019

Oh, this was great! I didn't have much exposure to distributed processing jobs. Really great to learn about staging, automating and tuning these jobs. I hope I can apply this professionally soon.

LY

Mar 01, 2019

This is very handy course compared with other cloud platform where a customized environment was provided without concerning setup it on my own. This is very thoughtful and I'm very appreciated.

フィルター:

Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform: 76 - 100 / 469 レビュー

by Liam M

May 09, 2018

Exceptional - If you understand how machine learning works conceptually, then this course contains labs that will teach you how to apply basic concepts using Google's API. In my own circumstances, I believe this information is applicable to the enterprise space.

by Shashank G

Dec 09, 2017

Very nice

by Alaeddine B

Sep 20, 2017

Very instructif

by francisco q

Aug 19, 2017

Great beginner tutorial on dataproc and leveraging GCP for big data. It might not be that straight-forward if you do not have experience with Hadoop or Spark. But I found it very insightful and I will be building some solutions using dataproc and cloud ML

by Yu X

Oct 02, 2017

great labs.

by Davide

Nov 27, 2017

Deeper inside how to user all the GCP applications

by Victor C

Aug 13, 2017

Muy bueno

by Haitao H D

Oct 24, 2017

I find this course is very helpful for me to pick up the basics of Dataproc. I will definitely recommended to my friends/coworkers as a beginner class. I hope to see more advanced course related to this topic.

by Daniel S d A

Oct 02, 2017

Very Good!

by Colin A

Oct 06, 2017

great overview of dataproc / hadoop implementation on GCP.

by Thiago B

Nov 07, 2017

Muito bom!

by Gord N

Jan 13, 2018

great stuff.

by Nataraj P

Dec 04, 2017

Thank you very much for this session

by Vladimir E

Oct 20, 2017

very nice, thx!

by Pat G

Aug 26, 2017

Great fun!

by Victor S

Apr 27, 2018

Really complete and easy to understand

by Kalyan K

Sep 12, 2017

This course is very useful and got good understanding on Dataproc and ML API's like Translate API,Speech API,Vision API and NLP API.

by Abhishek Y

Apr 26, 2018

Excellent to start with these components. Great tutors.

by Ajit K

Nov 01, 2017

Use cases were really good and the scenario based examples. Really impressed.

by David N

Nov 10, 2017

Excellent course! :)

by Shreyas R

Jul 18, 2017

Excellent Trainers , Excellent training!

by Anumandla H K

Oct 30, 2017

good

by Laurent V

Jun 18, 2018

Great content!

by Cesar M

Jul 06, 2018

Very good, a little basic but enough for the time needed. The labs are excellents, with test google accounts.

by Chris P

Dec 29, 2017

Really enjoyed it, woudl have liked to spend more time with the APIs and integrate with real time web downloads. There are a few bugs and misprints, but wasn't too hard to find them.