Good course to learn the jargon of ML-OPS will definetly give you good pointers to think about things you encounter daily on the job as a data scientist or ML engineer. Wish it would have been a little more technical.

Good general info but a bit basic for anyone who has already worked within the modelling pipeline. Nevertheless, Andrew is a great teacher and I did learn some new concepts and things to think about.

Good refresher if you already work in ML. A bit longish and could have been shortened.

I found the code provided useful to remind the use of Keras

In short, solid but not super mandatory

I like the acknowledgement of the importance of data quality. Machine learning is much more than just training models. Real benefits can only be achieved when moving to real life data

Very well explained. However, I feel that problems related to structured data are underrepresented though being extremely relevant for business in an enterprise context.

Great course to get started into production, loved the philosophical discussions on building ML models for production as opposed to ones developed for industry

Theoretically worth watching... but lack off hands-on excercises.... It would be more helpfull if there were any open sourse tools thought in the course...

The methods are generally helpful. I would have liked more overview of available paid and open source tools, even if no specific recommendations are made.

Ecellent course. Although very focused on unstructured data and deep learning, so if you are from a structured data background, you might feel left out.

Introduction to MLOps of deeplearning.ai, the course is a very good introduction and overview (even though no IT skills are learned at this point)

The course was very nice though for a Course that is part of a Specialization Course I found it to be too basic, even for an introduction.

The concepts covered were really usefull and informative. But it could have been a chapter in a course rather than course in itself.

It's great course for you learning about the process build model and problem that your model was created for its.

Too much story. It would be really great to see some codes and practical visual examples on real world issues.

Great course touching on some big topics in ML. I would like to add more labs and their video breakdown.

It's better the course has some coding assignments to comprehend the ideas which is shared by Prof. Ng.

The quizzes are meaningless, often ambiguous and the answers sometimes wrong. The videos are useful.

Some project plan / exercise / case study to be solved would have added more to the experience

Good course, yet I find the content a bit too generic and lacking practical advice on tooling.

inhaltlich und didaktisch eine sehr gute Einführung. Etwas mehr Praxisanteil wäre hilfreich.

This course is good for understanding the basic process required before developing ML model.

Worked well in shifting the view from modelling into data. Worthwhile for that reason along.

So far this course has been pretty great. Nifty Labs with a lot of useful info and methods.

Quite basic, but still useful introduction to following courses of the specialization

Useful course for understanding how ML works in production in an iterative approach.