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Вернуться к Google Cloud Platform Big Data and Machine Learning Fundamentals

Отзывы учащихся о курсе Google Cloud Platform Big Data and Machine Learning Fundamentals от партнера Google Cloud

4.7
звезд
Оценки: 12,615
Рецензии: 2,254

О курсе

This course introduces participants to the big data capabilities of Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud....

Лучшие рецензии

VS
2 мар. 2019 г.

Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.

AD
23 сент. 2019 г.

This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.

Фильтр по:

1651–1675 из 2,226 отзывов о курсе Google Cloud Platform Big Data and Machine Learning Fundamentals

автор: Vinay T

10 авг. 2018 г.

It was really a great course, I learned a lot and special thanks to instructor for helping in every possible aspects especially in labs part. Overall it was really a great experience.

автор: Rapheephan N T

26 апр. 2020 г.

Course was well prepared with introduction video, reading resources, and especially the lab which helped me easier to understand the concept of data engineer and ML in Google Cloud.

автор: Chris V

9 нояб. 2019 г.

labs were very well organized, although could have encouraged the student to do more troubleshooting. content was at the right level and instructors were very clear and informative

автор: Alberto B T

8 дек. 2019 г.

Nice introductory course. The only problem I find is that exercises are really easy to solve so learning is basically based on theory found in videos. It should be more practical.

автор: Christian H

23 дек. 2017 г.

Very good overview of the data tools on GCP. Not coming from data science it really pushed me to understand and see why a particular tool was used instead of another. Thank you!!

автор: Naiara A C

29 апр. 2020 г.

Eu gostei bastante do curso, mas acho que são muitas ferramentas faladas durante o curso mas entendo que esse é o objetivo. Dar uma introdução sobre variados serviços da Google.

автор: Sunuk P

18 апр. 2017 г.

Some latter sections felt as if they were not shot in sequence, thus disrupting the flow. This fact notwithstanding,

the program is an overall a good overview of the platform.

автор: João A

9 мая 2020 г.

In the second lab there is a minor error on a script. Solution is in the forum. And I felt that the third lab could be easier of understanding if it's used a simpler dataset.

автор: Alfred M

24 февр. 2020 г.

Some of the labs were cumbersome.

In another case a file name was inconsistent between the instructions and a script, easily corrected but maybe disorienting for some users.

автор: Miguel P F A F

18 нояб. 2019 г.

Great course. It is a great introduction to the basics of GCP as a foundation to ML. However, the last lab was not working well which, I believe, was only a temporary issue.

автор: Duy N

11 нояб. 2019 г.

A bit too basic course, but cover most of the fundamentals of GCP Big Data and Machine Learning. Would be actually much nicer if the course is a bit longer with more detail

автор: Rahul K

10 февр. 2018 г.

Could have presented better, giving overview of the architecture of all modules would have given us(students) better insight. We could co-relate things in much better way.

автор: Matthew M

14 янв. 2018 г.

Great course! Would have given a 5 star if videos were edited better (I feel you may have forgot to edit out some parts of a few videos - where errors occur for example)

автор: Seyd H

24 мая 2018 г.

Good course. Needs some updating as it would seem that some of Google's internal code is not provisioning correctly. Can be completed with a minimal amount of IT skills.

автор: Tushar G

9 июля 2019 г.

It was a good experience while learning with Google, but with this course they can go with much more basics like in the Practice session for more better understanding.

автор: Johny J

28 нояб. 2018 г.

Basic understanding of all the tools available from Google Cloud for Big data and machine learning. Really informative for knowing the right tools for the right jobs.

автор: Sandro B

6 мар. 2019 г.

Great introduction course! Please be more explicit in the Quiklabs integration in Coursera since is not easy to know how we need to "Run the Steps" and pass the labs

автор: Oleg L

18 авг. 2018 г.

The course was great, except for the issue with lab completion - had to do two labs twice. Well, at least I will remember the steps better - practice makes perfect.

автор: louis d v

26 июня 2018 г.

The data begins to be a bit outdated. I wish the course could cover some CLI commands instead of doing everything through the console. Still a nice introduction.

автор: yugo g

4 апр. 2017 г.

Great course with real projects and examples. and easy to follow. It would be better if you also provide the slides of this course so i could read again. Thanks.

автор: Sachu K

3 дек. 2018 г.

This course has helped me to get an idea about the fundamentals of cloud environment and its working or more specifically google cloud and it various services.

автор: Sriranga A V

27 окт. 2019 г.

Good Course for Fundamentals on Big data Platform and Big Query capabilities. Great Insights on ML and it gave a focus on how ML works and benefits on Auto ML

автор: Ronald F M S

17 мая 2020 г.

great, i enjoyed laboratorys and could try for free how to use the solution from gcp. I had some issues at laboratory that I reported for improvment. Thanks.

автор: Felix T

21 дек. 2018 г.

Excellent overview of the cloud ecosystem in the Google cloud. It moves rather fast across complex topics, but in a very careful way of connecting the tread.

автор: Pascal A S

28 мая 2020 г.

Solid. The AutoML part is a bit too easy. Ideally, you would provide a link to the repository containing all code used. Specifically, for the Keras section.