The Good: The instructors were clear and concise and provided just the right amount of context and justification for the concepts they presented. The Bad: The labs were very burdensome, unstable, and provided very little toward the learning for the course. Even worse: The Qwiklabs experience, having to interact with their support multiple times, was unbelievably frustrating; Bad enough in fact that I doubt I would ever take another Coursera course if it is coupled with Qwiklabs. Very unfortunate.

The labs are broken and you cannot complete this certificate following instructions.

And if you don't follow instructions you can get banned from the labs.

Join this course at your own risk.

Quicklabs support is poor. Labs fail to implement (labs in weeks 2 and 3). Instructions are not clear for some labs. This is the las module in this specialization. It is pity that the last module wasnt implemented well and spoils the whole impression for the entire course.

After going that far in this specialization, the lab week 2 asking to bind a trigger to github was the end of my journey.

The course content is advanced and great for theoretical learning. The practice labs and support by Qwiklabs make it a 2 star course as the

1) content of the labs are not updated to the latest vertex AI platform and outdated

2) the python virtual environment package dependencies are insufficient

3)the Qwiklabs instances that are provided are not powerful enough to complete labs in the given time.

4) Support from qwiklabs point to the same lab instructions but no additional inputs to fix the issues

Also, the issues mentioned above have been outstanding for over 6 months and unfortunately this course is not updated and is a blocker to earn the Coursera GCP ML Professional Certificate.

I have tried each of the labs 2-3 times but could not complete them due to above

On the positives, this is good course for advanced practices and capabilities of ML pipelines on GCP. Also, this is the only course that I had challenges finishing labs and I completed labs of 8 of 9 courses without issues seamlessly.

Thanks Coursera and I hope Qwiklabs revises the content

Labs are poorly written

Lots of issues

qwiklabs provide only standard solution which doesn't resolve any issue

Averagae turnaround time of qwiklabs for tickets are pretty high (more than a week) for any bugs in the lab

They are pretty fast in the quota related issues

Expected some reliability for google courses!

Solutions are not provided in lab in correct manner. thers is no solution availabe on internet .

Labs are so full of bugs and instructions are not at all clear.

poorly designed labs require self writing lab code that is not intended.

dysfunctional course

Content was more like monologue, having proper video/animations would certainly help to new users who are new to these concepts. I felt like some monologues are just going on and people are simply reading their contents and assume people are pro on the other side. I would have loved some interactive video explaining concepts or any animation video where I can see things are working

The course is fine but guided labs little out of sync for the content.

Half the assignments don't work. Staff do not even reply to the discussion forums. DO NOT TAKE THIS COURSE!

- Pros: interesting topics were touched - Cons: 1. Presenters are "talking-heads" reading documentation-like script 2. Slides are detached from what presenter is saying and rather distract because one have double cognitive load: follow monotonic presenters talk and align it with "managerial Comics" shown on the slide 30% of a time. Other 30% are random code pieces, rest 60% is something truly useful. 3. Labs aren't possible to finish by following instructions. Mostly because they are outdated, which causes dependency hell and errors here and there. Even by googling, applying hot-fixes and hacking the packages I wasn't able to get 100% of them done.

This course is unfinishable, the tech support is unhelpful, I originally flagged an issue with the graded labs on 13 Mar and as of the writing of this 3 July, it has not been fixed and I am unable to complete the course, preventing me from getting the completion certificate for the entire course. Don't waste your time taking this course.

This course is filled with labs you cannot complete as they refer to old GCP components that fail to complete and hang silently. I would recommend waiting until they fix the lab coursework for this class.

Although insightful, many of the labs have problems which you need to debug on your own.

Labs don't work! week 2,3 and 4.

Many of the key labs required to complete this course use outdated packages and instructions that will not work. Completely impossible to pass the course without extensive version troubleshooting at a level more advanced than the intended audience. I would consider this course broken and would never recommend a new user enroll.

Very complete course that dive deep into the functioning of TFX pipelines, orchestrations, CI/CD, showing tools and resources we can use to automate the maintence of ML process. Thank you all for this.

This is a great course to learn how to apply MLOps principles in large scale machine learning projects. I'll refer to this course in the near future to bring its concepts to customer ML platforms.

very nice and easy to undertand concepts , hope for more new such free contents , thanks to google , quicklab , coursera for providing this opportunities .

Clearly elaborated

Very good, thanks!