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 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
By Marvin G
•Jan 15, 2024
I am somewhat disappointed with this course, This MLOps process involves a wealth of information and almost None, hands-on practice, the presentation here condenses everything to the point where the valuable details are lost. The instructors, who are knowledgeable, deliver the content in a rushed manner, and the labs are essentially a matter of copying and pasting without much room for meaningful coding or engagement. The provided code appears to be a compilation directly from documentation, making it a simple matter of running the notebook without much challenge or understanding required. The course is 45$ per month, therefore there's little flexibility as falling behind means extending the learning period to X months (no time to practice the lesson learned). The examples presented, such as the MINIST database and supermarket database, feel repetitive without showcasing real-world scenarios, and everything is using TFX. If your goal is to grasp concepts and gain a broad overview of MLOps, this course might suffice. However, for a more practical and challenging experience, I recommend exploring IBM courses, which, although demanding, offer a deeper and more meaningful learning experience.
By Tman
•Apr 22, 2023
Well, I am a big fan of Andrew Ng, his initial ML course is what kickstarted my career change from a computer scientist to an established data scientist, I quite liked the Deep Learning Specalization, but this course is absolutely not what I hoped it would be. Most of the topics talked about have very little relevance to MLOps. To name a few: Auto-ML, Dimensionality reduction, quantization, pruning, distributed training, knowledge distillation. All interesting topics, not this course is about MLOps, Put these topics elsewhere. And the topics that are related to MLOPs imho (Monitoring, Model debugging) are discussed very superficially and always, ALWAYS are the different google products promoted. I don't want to pay for a course that then spams me with advertising. Plus, the practice exercices are ridiculous.
By Longlong F
•May 27, 2022
In the C3W3 lab, the status of the pods never change to 'running'. I had to re-do it many many times and but still didn't get the score. I am really sick and tired for these course. never again.
By Associação F P R
•Sep 13, 2023
The assessments are not well-paced and most of the lectures are not useful in terms of linking the theoretical knowledge to the practical knowledge.
By Sagar S
•Oct 14, 2022
Some notebooks are too many dependency problems and it takes forever to correct them.
By András M
•Oct 11, 2022
Complete waste of time.
Misleading Google propaganda combined with broken tools.