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Course covers the fundamentals of GCP with TF. Although the labs don't require much of a coding, and the ones which require have a poor structure because after each subtask say Task 1, you should be able to see if your code outputs the correct output, so for that they should have included some testcases. Also in the training part, quicklab has limit of 2 hrs, but training takes about 40-50 mins for a lower input size, and that lab requires to run training 3 times, so I was forced to just trim down the input size to fit all tasks within the lab time limit.

great survey of it. optional labs should be mandatory I think. Also it would be nice to have a end to end walk through in summation. another option to complete the mental model it to map notebook sections to the GCP infrastructure in a presentation.

I wonder about cloning the gcp repo locally to use it as a local template to further study. In other words I fire it up in my account later. or I access GCP via anaconda jupiter. Just wondering.

Great course. I knew about machine learning but didn't know how to make a production system. This course helped me to achieve that goal. Now, I am confident of the fact that I can work in this field and work in a company. Only thing which needs to be taken care is about the coding part. We don't get hands-on, though I realize it will be difficult to do it at first attempt and in limited time. BQML is also very handy.