Covers a lot of hot topics related to ML Modeling pipelines in production with great breadth and depth.

This is very helpful course to understand the life of model specially after its deployment.

This course filled in some black holes in my knowledge and I found it very helpful.

Excellent!! Ver, Very Very Good. Learn a lot. Thank you for sharing.

Excellent introduction to pipelines for production ML.

Great course, probably the best in the specialisation.

The first course of MLOps, and the best.

Really liked the last week content

This is a very detail course

great course, a lot of stuff

Good content and hands on.

Amazing course!

Awesome Thanks

haved fun!

Nice !!!!

Good

What's Good

- The selection of the topics for the programming assignments is outstanding - I am very experienced at completing QwikLab assignments with ML Pipelines and I still learned something new.

- The topic coverage is great - I learned a lot of things in the field that I was not aware of.

What can be improved

- The lectures are being read from notes and it's hard to listen to without increasing the playback speed to 2x. I think there should be more readings and the videos should be more engaging (i.e. like the GAN specialization's lectures).

- The quizzes should count as part of the grade. It's possible to complete the all QwikLab assignments within a couple hours and the entirely of the course completion credit is based on that.

Very nice course. The reason I graded it as 4 (and not 5) was related to the educational value of the labs based on Google's console. Per se, the exercises were flawless but I felt like I was just running the steps without much understanding of what I was doing.

Yet, an awesome course. I learned a lot! Thank you very much!

Great course, you can learn new concepts related to MLOps and new technologies like major Cloud vendors, packages and platforms like TensorFlow for the ML model. I would like to have more exercises to apply the various terms and processes seen during the course

It covers a vast territory of material. However, there is plenty to learn in terms of concepts. Some of the graded labs can make you dizzy. Overall, it is worth the effort. Get a financial waiver if possible.

There were a lot of useful information and practical insights about the subject of the course. The material on Tensorflow-specific modules felt a bit unorganized and cumbersome to go through.

Lots of hands-on exercises accompanying knowledge learned in this course 3, but could be difficult for someone without prior working knowledge on Google Cloud platform/services.

The assignments are just quizes, and no practical programming exercise

Good but I think that is much content for low time

Many important concepts and topics of MLOps are discussed in this course, although there's too much focus on Tensorflow and associated libraries/tools. It would have been better to have hands-on with other MLOps open source libraries and tools.