The course was fairly compact and you would be able to finish each week lesson every day if you eager to do so. It was fun and educational. I loved the surprise in the last question of the optional quiz in week 3.

Great course explaining concepts on ML lifecycle and deployment, especially touching topics like concept and model drift, monitoring models, error analysis, experiment tracking, pipeline and lineage. I loved it.

This is a great introduction for how the mature machine learning product could be morph into mature products with multiple challenges. It helps me a lot for understanding how future AI industry looks like !

This course would be very useful if you are ML-engineers, data scientists. However, this course does not teach you how to code. To code, you need to take Deep Learning specialization or some other courses.

Very practical materials and application-focused methodology! A lot of rule-of-thumb gathered from ML pipeline experiences. Clear definition on acronyms and mainly easy-to-follow non-technical guidances.

I think you should never start applying for any ML jobs until you take this! a lot of things that I've been doing - were that based only on my intuition - are now so clear and systematic! Thanks Andrew!

Very valuable course for those who already have some knowledge on machine learning or AI applications. Very close to what systems engineering processes recommend, as when seeking ISO15288 compliance.

Excellent course. Happy to reconnect with Andrew after a few years to continue my ML journey.

Full of useful tips & tricks, but also deep thoughts on how the ML community should evolve its practices.

Excellent course, as always. Very well explain for both Data Sicientist, Software engineer and Manager (with some basics undertsanding of ML). One of these courses that Data Sientist should follow.

really a great course. It'll really change your way of thinking ML in production use and will help you better understand how can you leverage the power of ML in a way that I'll really create a value

Introduces you to the basics of MLOps in a well paced mannar. Would request to add more examples of structured data sets, as many companies usually are dealing with the related problems.

I really enjoy participating in a great class like Andrew's class. It's full of useful and applicable points that I encounter during a real prj.

Thanks for sharing this asset with us :))

The content of this course has been especially useful for me. I wish there were more emphasis on the tools recommendation as well, but the theoretical knowledge was just fine. Thank you!

Practical and well-structured advices throughout the lifecycle of ML. Examples from real world problems & experiences make the advices more tangible and helps to reflect on own problems.

Andew Ng is truly a world leader in the field, the way he approaches the subject and the explanations he gives are truly unparalleled. It always a pleasure taking a course he instructs.

Good intro on key concept in MLOps. Would recommend it to anyone who is stepping into this field as well as for ML Hobbists to understand the main challenges of a ML production system

This is a great course to learn many practical procedures and techniques, to apply ML algorithms to real world problems and do it well, by avoiding common mistakes and deliver value.

A great start with respect to the MLOps specialisation. If anyone wants to take this single course, then not a lot should be expected because this is only a start to the main MLOps.

Excellent course! Andrew Ng is an exceptional human being. His teaching skill are impeccable and you as a student actually are interested in what he's telling you and learn more.

Wonderful and practical MLOps introductory Materials. Very systematic and useful! Always appreciate Dr. Ng uses the most easy to understand language to explain difficult problems

I would recommend this course to anyone who has to implement models in production. It is an introductory course but it does have a few key concepts that are good to keep in mind.

An excellent start for becoming a Machine Learning Engineer where one learns about the complete lifecycle of a machine learning project from scoping to deployment to monitoring.

I learned many new perspective on how I can build my machine learning product and some pitfalls that could happen. It gives me fundamental on how do I design my product better.

This course helped me to organize my knowledge, and showed the questions that I should regullarly ask to either technical, or business teams to create valuable AI-based product

The course helped both validate what I knew about the topic and update me about many new trends/tools via high quality references + first hand experences from the instructor.