it was good to learn

Good intro but it looks like in other courses from deeplearning.ai, while they teach you something, they also try to "sell" people a specific framework. In this case, they seem to be selling TFX. I still recall how they sold people the Trax library in the NLP specialization which has replaced Trax with huggingface. I take what is useful from these courses but I distrust their agenda.

boring and kind of wasting time. I mean, learning course 2-4 is enough ,why there is an extra "outline" course here? Also, the content is a duplication with Andrew's other courses in coursara.

Good overview of best practises, but still a bit too general and non-technical.

It seemed a little too general. I would've liked more labs.

do not meeting the expectations

I had a great time learning with Andrew in this Introduction to Machine Learning in Production online course. In 3 weeks, Andrew walked me through each step in the machine learning project lifecycle and shared many best practice tips (from years of experience of his own), which I felt could be directly adopted and applied.  I especially appreciate Andrew’s emphasis on a data-centric approach and raising human-level performance. There are two valuable and practical suggestions to increase your machine learning model accuracy and contribute to a successful ML project, which have not been given enough importance in practice. As always, Andrew’s friendly, clear, and concise style and his capability to explain complex ideas with simple language made some of the seemingly intimidating subjects easy to digest. 

I am thrilled to have completed the course "Introduction to Machine Learning in Production" on Coursera! It is the first out of four courses in the Machine Learning Engineering for Production (MLOps) Specialization. It was a great introduction to key concepts in ML Lifecycle, data pipelines, deployments, and MLOps workflow. It is well-structured, easy to digest, practical and uses examples from real world problems & experiences to build a strong intuition and foundation on how to apply MLOps principles to real-world problems in production. I'm excited and looking forward to putting these skills to use in my career, current projects, and also to continue learning more about this fascinating field.

Dear Andrew Ng, Your course "Introduction to Machine Learning in Production" on Coursera was fantastic! Your teaching style is exceptional, and your ability to explain complex concepts in simple terms is truly remarkable. The course content was well-structured, and the real-world examples you provided were incredibly insightful. The part where you mentioned the gap between MLE metrics (such as accuracy) and business metrics (such as revenue) was impactful. Your passion for machine learning is contagious, and it's evident that you genuinely care about your students' success. Thank you for creating such an outstanding course and making a positive impact on my learning journey. Best regards!

This course acts as a very good guide in helping one improve the most important thought-process aspect of the project development, that's vital to work in the field of ML and AI. There are countless videos and tutorials on the internet today, that will help one learn the technical skills. But this course provides a shortcut to learn thought/project development process aspects which are usually gained only through years of experience. The best part was, all the concepts have been explained by taking a real-world use case, which makes the discussions non-trivial and practical.

This course is beyond just Introduction, Andrew has certainly has given me all the perspective of production level readiness for an ML Models and the strategies MLE must follow before heading for production rollout. This course definitely gives the confidence and the knowledge to progress on ML Career. I would recommend anyone wishes to start there ML career , this course is a must before stressing to much on just creating ML models alone.

Special thanks to Andrew and team for this amazing Course.

BR, Amit Kudnaver

Thanks deep learning AI and coursera for providing such a great content on an evolving field of MLOps. For anyone interested in exploring the challenges involved in getting machine learning models into production and a set of best practices that can be taken to overcome the challenges and get better model performance in production environments covering many real project centered examples and labs to practice on, it is definitely worth spending time with and working through it.

I recently completed the Deep Learning Specialization and found this course to be the perfect complement. It filled in all the gaps from a big picture perspective and provided valuable insights on how to start a deep learning project, how to identify if a model has a problem, and more. I truly enjoyed this course and found it to be very helpful. Many thanks to Andrew Ng and the DeepLearning.AI team for creating such a comprehensive learning experience.

Andrew NG is the best! He is an exceptional educator and a true expert in the field of machine learning and artificial intelligence. His teaching style is not only clear and concise but also incredibly engaging, making complex concepts accessible to learners of all levels. His passion for the subject matter is evident in every lecture, fostering a genuine interest and enthusiasm among his students, including me.

Found the course really helpful as it uses a lot of examples to better explain importance of some steps or their appliactions. I was surprised to see some issues that I worked on for weeks discussed here with a good way to address them and those were quite similar to what we did but took lot longer.

This course is really great to help you make better decisions based on some standard practices and guidelines.

Excellent content and explanations, as always Andrew Ng proves to be enormously valuable and effective in conveying concepts in an easy and very actionable way.

The course contains many practical tips that every ML team should know by heart. My experience of multiple years in the field suggests that this is not always the case, and that team would have a unique opportunity to improve adopting these concepts

Andrew Ng presents a very thoughtful and insightful look at production issues in machine learning. His insights answer a lot of the questions I had after finishing a bootcamp elsewhere, although I might not have been prepared to understand everything he said if I had not taken that bootcamp.

His tone is very reassuring and intellectually stimulating, despite pronouncing all 'c's with a 'z' sound. :- }

As a ML engineer, I though this introduction course would go "meh" for me before jumping to more advance courses in the specialization but no! I have learned a bunch of useful techniques to consider before training a model, collecting a data or even deciding what to work on in the first place. I don't know about the rest of the specialization yet but this is a must tool for the trade folks.

Excellent. Andrew has a capability to teach in such a kindly way that makes the course so pleasant and inspiring !

Moreover we can notice all the experience he has and I felt so grateful that he shares it with us. Thank you so much ^^ That will defenitively help my journey in data science, and I was touched by his end words : don't use AI if it is not helping people. Promised, I won't ^^

This course offers invaluable guidance sprinkled with Professor Ng's generous wisdom. I gained a structured understanding of how to conduct a Machine Learning project from scratch to deployment. I already had extensive knowledge of ML/Deep Learning and Data processing, but this course has provided guidance on where exactly to apply my scattered knowledge.

Andrew Ng is one of the top instructors I have ever had in my life. He is extrodinarily clear and his thoughts are organized. The content was also very good. I have been building ML systems for years and he gave words and clarity to ideas I intuitively know, and pointed out a number of really solid new idea, allowing me to better communicat to my team.

Excellent course. As always Andrew makes the content of the course engaging and brings us new ideas and concepts. I would love to easy Andrew on the other courses as well because unfortunately the next courses were not so engaging. The content was delivered by just reading the slide and there only was slight explanation of more advanced concepts.

Great way to get introduced into the steps of building, deploying and maintaining ML algorithms in production. The presentation was clear and concise, without ambiguity and with a lot of practical insights. Very useful and relevant for individuals working in the ML industry.

Very happy with all courses taught by Andrew 👏

I find this to be a very philosophical approach to Machine Learning, especially where Andrew NG poise questions that will make you rethink entirely the way you've previously approached ML Problems. The explanations are broken down in a manner that makes it so seamless to grasp. Thank you for this opportunity.

Genial, es un gran curso, 100% recomendado. Es difícil, incluso en escuelas de posgrado, encontrar un curso que cubra estos temas en Latinoamérica. Los temas que se abordan aquí sin duda tendrán un gran impacto en los próximos años. ¡Gracias por democratizar el conocimiento y ponerlo al alcance de todos!