last lab run out of the time

very interresting, cheers

Very beginner friendly.

go beginning with labs

trop guidé dans les TP

Just too soon for me

Some labs are buggy.

very well completed

Muy bueno el curso

Good introductory.

Very fundamental.

Not deep enough

Good Experience

no challenging!

Average course

Intermediate

Too basic

not bad

Good

good

I did not have a good experience with this course and wanted to provide this feedback to the team. From an educational standpoint, I could see the intention to create meaningful projects and provide hands-on experience. The videos are easy to watch and the instructors seem genuinely happy to record them. From a delivery standpoint however, that is not done very well. I had difficulty operating the labs, mainly with Cloud Shell being stuck at provisioning step indefinitely. When that is the first part of the lab, it stops you right on your tracks immediately. Even in the one case where it worked however, I could not understand the reasoning behind a timed lab. Isn't this supposed to be an opportunity to explore all the impressive capabilities of GCP? Having a timer, just forces you to go through the steps, copy-pasting the SQL queries and answering the questions, in which case I would've been happy to watch a screencast instead. With the setup processing being a hit-or-miss, wouldn't a single temporary account be better, so that the students would only have to set up the environment once? If anything, that would be a tremendous learning experience, to go through the steps of setting up everything carefully, just like setting up a local development environment. There is a lot of room for improvement in this course, especially being the first one in the specialization.

Good overview of all the services, but I could have read it just from the service list, and all the labs can be done without watching this course. There is no barely any information about machine learning, except for a small Tensorflow playground overview and copy pasting Python to Datalab. But this negative comment is only because I was expecting it to be a bit more comprehensive, for someone who has no previous information about any of the subjects, this can be a good introduction.

This course was all over the place. I signed up to do the GCP Data Engineering course, and this was a HIGH level intro. that also jumped randomly into ML without giving a whole lot of insight into the actual. GCP env. They skimmed over 90% of what an actual project would consist of-- data cleansing, ETL, data insight, etc. There didn't seem like there was a cohesive plan on what they were covering.

comparing to other Coursera courses this one lagged behind. Unpolished videos, too much time spent on the promotional aspects of GCP, and the examples given were more of a demonstration in a style of follow me. Adding to it my expectations that Google should outperform, I was quite disappointed. However, the content was important for me and I don't regret taking the course.

Personally for me this is a very badly structured and shallow material that I have big trouble concentrating on. I prefer material in big contiguous chunks. Small videos, parrot-style codelabs with no challenge and scattered cross-linked documentation is the opposite of what works. Sadly there's no book or compilation that covers ML spec curriculum in-depth.