- the lectures are not easy to follow sometimes, might be better if the code is shown more step by step rather than being shown all at once and then the instructor arbitrarily starts explaining from a particular location.

the labs are either too easy or such that there isn't enough information to find out the answers unless you really do arbitrary try and error. Either way you don't come out learning much.

Lectures are good but the labs are just tapping shift +enter on jupyter notebooks (There is no really hands-on). Some intermediate steps on notebooks are not well explained. For learning is ok , but having to pay for a certificate on this , I wouldn't recommend it

Exactly what it says. Labs are trivial and I felt like I didn't learn much other than how to use the interface for serving and taking a model from start to finish. The core concepts are useful both in GCP and if you decide to roll your own stack

Good to work in a real world environment, though not much hands-on work (most code has already been provided). Still not familiar with API's details.

This course is not very practical nor very well explained. The topic is very interesting but it is not delivered clear enough.

I am satisfied with GCP training except for some errors.

I think I need the latest update.

more explanation about labs were needed for help to understand the code

the course is helpful for any learner initial to touch GCP learning

Deployment was not successful. Was not able to debug

The labs could have been a bit more useful.

Some codes of yours notebooks doesnt work

Some labs have to be reviewed and updated

QuickLabs has error in many labs

thank you

well

nice

Really, really poor due to the fact that it's outdated to the point being broken in various ways. For instance, Qwiklabs confirms there is a bug in the local prototyping lab that prevents us from actually training anything. There is no consensus between video and lab as to whether we are using Keras or Estimators. Lab 5 points to an old ipynb using Estimators, while Lab 6 assumes we have used a newer version featuring Keras--so one redoes all of Lab 5. There is a "Optional Lab" with accompanying videos, but where there is no option to do the lab--the lab has been removed for half a year or more (per the discussion board). The video summary mentions that we have used App Engine to make a frontend for our model--no we didn't! I understand having a few bugs, but this course surely wasted several hours of my time. And yes, as others mention, the TODO's, for the most part, don't require much thought. On the upside, I think Lak is a really excellent presenter, and that Chris and the other guy are also pretty good.

Course content is good. But Coursera policy is bad. After completion of the course, only a 1-month extension is given to revise it after that. You cant see the content. This is very bad. It would be better to download the videos.

How are you supposed to revise the contents?

After that, you have to pay again. I will think twice before going for any course with coursera.

Some content is out-of-date and the labs are mostly solved with no much guidance. I was expecting a better explanation on what are the key points in the labs, such as the commands needed to create training jobs and so on.

Good content, but flawed lab design. The labs are designed to run in sequence and have dependencies from previous labs. Those dependencies break with different sessions of Qwiklabs.

Videos were helpful to get to know Google Cloud services, but the labs were a mess with different versions (deepdive vs deepdive2) that were not a pleasant experience.

Most of this course lack the actual coding so I dont think I get much actual experience from this course

The labs were completed, I need to only run them. which I think I couldn't engage myself

The Lab tests could be more interactive, and the tests could have more questions.

The labs are not good. The labs can not evaluate a student.