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.

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.

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.

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

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 good, thanks!