Not enough hands-on labs. Mostly just videos and running existing python code. Had to write only a tiny amount of code. I won't remember any of the code, I'll just remember ctrl-enter on all of the pre-written python.... could definitely use some improvement.

Would be nicer if students can use the google cloud with less restrictions. I got blocked multiple times from trying the codes in the videos..

Overall, the materials are great and very interesting!

Objective of course is great. But, a lot can be improved in terms of clarity on how to execute this course. It is not clearly mentioned whether we need to just execute provided notebooks or write code from scratch. Moreover, how to copy these notebooks from Google cloud repo on github is not mentioned anywhere.

Definitely adds a unique perspective on thinking about machine learning systems at scale. This course is suitable for Data Scientists, Data Engineers and Machine Learning Engineers.

One of my favourites Courses from Google, it provides an excellent overview of the End to End Machine LEarning process, and how to use GCP to speed up your workflow, highly recommended to anyone looking to expand their understanding of Real World application of ML

The course is well structured. However, Google moves really fast when creating new products hence there is some confusion when running the labs. That being said, it's amazing that qwiklabs is utilising essentially a live environment for practice.

QuickLabs has error in many labs

Excelente didática e práticas para aprender fazendo. Muito bom.

pretty good for intro to get a feeling of how the Machine Learning System is working as a product.

This specialization consists of 5 courses:

Course1: End-to-End Machine Learning with TensorFlow on GCP

Course2: Production Machine Learning Systems

Course3: Image Understanding with TensorFlow on GCP

Course4: Sequence Models for Time Series and Natural Language Processing

Course5: Recommendation Systems with TensorFlow on GCP

In specialization's FAQ say nothing about "audit" option. Do You know what is it ? "Audit" means that You can use course video material even after You subscriptions ended.

By fact, only "Course 1" has such ability. Before pay for specialization, carefully check FAQ for EACH separated course in specialization:

courses 2-5 has special point:

"Why can’t I audit this course?

This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

"

"Who have paid" means that after You subscriptions ended, you lost access to video materials in this courses.

p.s.

1 star only for "Audit", content and lecturers are rated higher - at least 4 stars

Labs were perfectly designed to get nice hands-on experience.

good

It was very nice

good video

Great

good

awesome

errors...

good!

good lectures~

what a wonderful course! thankyou so much!

so nice

Great Course with exposure to end to end deployment and Code Sample to learn Faster

well

I am satisfied with GCP training except for some errors.

I think I need the latest update.