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.

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.

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

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.

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!!

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.

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.

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.

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.

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.

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

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.

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)

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.

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.

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.

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

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.

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.

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.

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.

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

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.

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.

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.