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Learner Reviews & Feedback for Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform by Google Cloud

4,142 ratings
488 reviews

About the Course

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...

Top reviews


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.


Apr 23, 2019

The course has introduced me to hadoop tools. I have learned how easy it is to setup a hadoop cluster using Dataproc. Will sure look for cases that have implemented hadoop and replicate on GCP.

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1 - 25 of 484 Reviews for Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform

By Joe S

May 12, 2019

I think the quizzes should have had more questions, there were many more cool things you could have asked.

By Justin E

Jun 04, 2019

This course is far longer than any of the other courses in the Data Engineering specialisation. I felt that it rehashed a lot of the first course as well.

By haiyang l

Jun 22, 2019

Wish it went in more depth about RDD transformation, which was a little bit confusing... A lab about how DataProc can be used as an extention of BigQuery that does not overlap functionality would be nice. How to covert RDDs to Pandas DF, and vice versa.

By Ruth W W

Apr 23, 2019

The course has introduced me to hadoop tools. I have learned how easy it is to setup a hadoop cluster using Dataproc. Will sure look for cases that have implemented hadoop and replicate on GCP.

By Lun Y

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.

By Shivam S

Dec 23, 2018

Assumes the learner has an intermediate level understanding of concepts like Hadoop, Spark, HDFS, and python. Extremely hard to understand the concepts without background in the above mentioned items.

By Alexey M

Aug 11, 2017

Course lectures are mostly fragments of another course, cut in small pieces - many of them are less than 30 seconds long! Content wise, almost everything were discussed in the previous course (Google Cloud Platform Big Data and Machine Learning Fundamentals).

By 苏高生

Nov 27, 2017

This course is so bad that I do not want see again. I really think this course is an advertising of google cloud , and which only teach a little useful things. If my commit makes someone unhappy, but also hope forgive me. Thanks!

By Marc N

May 31, 2018

Videos are overlapping, some videos are not loud enough, descriptions are not fitting to the current version of the console, nearly all the same than in the fundamentals course...

By Yitao Z

Nov 27, 2019

This cource makes those mystery things tangible and exposes you to them by very practical approaches.

Very good construnction of lecture! Alway reviewing learned in the past together with stressing the coming point, this made my awared of where I am in the course.

I am happy to hear problem senarios from the course which I also used to face in daily practice. The related solutions are inspring.

In the lab sections, thanks for same practice approaches sticked throughout, I became very fluently in manipulating those operations for practice.

By Mark B

Aug 06, 2019

great job team. empowering material. only glimpses but also seeds/ starting points to start running with the tools introduced. room for improvement: better integration of readings with vids. better integrate the set of data proc- big query connectors w/ lab(s). perhaps more quizzes to drive home (section of) key points. thanks again for your great work.

By Aditya h

Aug 27, 2018

Teaches you how to interact with various GCP services - Firing up a cluster utilizing dataproc & CLI , utilizing Spark, Installing software on master node, how to utilize cloud storage so that you can make your clusters stateless. How to move data from dataproc to Bigquery by utilizing the connector as well as cloud storage as intermediary.

By Miles O

Oct 22, 2017

Found the topic a bit overwhelming at the beginning, but the videos were able to explain the topics very clearly, despite not having a heavily technical background. The labs were also very helpful in understanding the possible use cases for using the various GCP services!

By Peter B

Jan 29, 2019

The last question about which item was not suitable for ML, I would have like to see an explanation for the answer. Especially since less than half of us are getting it right. Why can't ML recognise an upside down product? It can be trained on that dimension, can't it?

By Rai S

Dec 18, 2018

I would like to have more extensive labs for Data Proc. Selection of pyspark for most of the course was quiet useful. A little bit more of dataproc use cases comparison of dataproc modules including spark, hive and then relevant proprietary options available in Google.

By Moses O M

Oct 16, 2017

Great Presentation on migration to GCP!

Great presentation of the capabilities that Google Cloud Platform provides for Machine Learning and the changes needed in architecting the ML solutions to leverage Cloud Storage as opposed to persisting data in the cluster nodes.

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 Wenyu Z

Jul 13, 2017

I was able to learn how to use dataproc and datalab in an effective fashion, and get first hand experience of analyzing unstructured data with datalab. Fantastic material!

My suggestion is to reduce a series of short videos for the same module into one video.

By Sabyasachi C

Sep 11, 2017

it was a great training on utilizing the GCP infrastructure to quickly wrap up analytics job. The concept of isolating data from processing is a great approach in the long run. The processing power coupled with ML APIs provided by GCP is definitely a winner.

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 Harold L M M

Mar 16, 2018

I liked this course very much, but, I think it would be better for all students if this course and the others based on codelabs, move to qwiklabs, which is a great training platform, and is already yours btw. Overall, this was a great course.

Thank you!

By Muhammad N B

Jun 30, 2019

I enjoyed every bit of learning in this course. I am getting better at understanding Big Data processing using sophisticated and state of the art GCP services. Warming up for Google cloud Data Engineer Certification. Your content is irresistible!

By Riebeeck v N

Feb 03, 2018

I enjoyed the repetitive nature give the mechanics for cluster setup and the sequential add on of information. I also like the fact that we are shown how to set things up by clicking around of the GUI and the corresponding cloud shell commands.

By Jafed E

Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand