JS
Sep 13, 2021
Excellent content and lectures from Mr. Robert . Thank you very much Sir for the excellent way of explaining these difficult topics . Thank you !!!
MB
Oct 20, 2021
I enjoyed this course a lot. It gave me a lot of ideas on how I can improve my models and make my workflow more efficient. Thank you.
By EMO S L
•Sep 29, 2021
Nice !!!!
By Diyorbek T
•Mar 18, 2024
super
By kothakota S
•Aug 17, 2023
Good
By Naveen K
•Nov 23, 2022
Good
By Vijay
•Nov 20, 2022
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.
By Shamiso C
•Sep 30, 2023
The course is great, the instructors teach exceptionaly well. I didn't like the qwiklabs assignments. The instructions were not so clear and also everything was just copy and paste, I would have prefered to do things through the coursera lab or google collab like how it was with the first two courses in the specialization.
By Fernando F
•Mar 9, 2022
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!
By Carlos A L P
•Jan 3, 2022
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
By V. A
•Aug 31, 2022
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.
By Giannis A
•Jun 15, 2022
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.
By Jerry Z
•Apr 4, 2022
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.
By AG S
•May 14, 2023
It is a great course but the QwickLabs are not really useful and sometimes result in errors and a waste of time.
By Suet Y M
•Jun 8, 2022
The assignments are just quizes, and no practical programming exercise
By Avinash R c
•Dec 10, 2023
very good course to understand the principals behind MLOPS
By Ruan L D
•Nov 19, 2021
Good but I think that is much content for low time
By Aero
•Jun 1, 2023
Good, but labs are quite complex.
By Mohamed N M
•Feb 9, 2023
MLOps Engineers are not Data Scientists. The course and the specialization under which it falls give the impression that the focus is bringing ML workloads to production, but this course went too much into ML topics. Certainly vital topics, but ML Engineers will have a hard time. Admitted, the boundaries aren't that clear-cut, but MLOps as it's trending right now is not the Data Science work itself.
By Shubhendu V
•Dec 2, 2022
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.
By Fares E
•Sep 23, 2022
Amazing course, very well explained and Robert is a great instructor however the assignments are just BAD most of the labs are bugged and or broken would be much better if the assignments were on coursera's platform
By Justin H
•Aug 10, 2023
The graded lab assignments are broken. :(
By Frank S
•Mar 17, 2023
Too vague, unclear questions
By Simon B
•Oct 3, 2022
I have to say that i did not like this course and I'm happy it is done. It is certainly not because the topics are not up to date or anything but it is the way it is presented. The slides are cluttered with buzzwords and nonsense and the actual content is only spoken. This makes the slides completely useless. From the labs, i learned pretty much nothing and will have to do another course about the same thing somewhere else.
By Yushi Y
•Feb 14, 2023
The material and the way to content is delivered is poor. If I were to learn something about "in production", I really want to SEE a real thing IN PRODUCTION, instead of some theoretical discussions or unrealistic and trivial examples.
By Fan Z
•Mar 5, 2024
Not very relating to production - it reviews different topics in ML and in introductory depth.
By Sagar D
•Jun 15, 2022
Disconnected