The key concepts taught in this course have entirely changed by visuals towards looking at data and it gave me clarity on how we should proceed in the very first steps. I will be starting with the other modules of this MLOps specialization as well. Hope to learn a lot from this specialization course.

I wish all product managers and C-level people took this course before starting AI projects;) Jokes aside, a lot of content in the course is very specific and will definitely help when you encounter those issues during development of ML projects. Looking forward to continue the specialization.

Very well structured course, informative, interesting, logical with clear examples, I have had a clear view of a life cycle of an AI project and tips and pitfalls, hands on opportunities to test step. Andrew always remind students their responsibility of being ethical, highly recommended.

Another one of Andrew Ng and DeepLearning.AI's amazing courses. The course was very well designed with plenty of helpful labs and practical examples that helped you understand the material well. I would highly recommended taking this course if you are interested in Machine Learning.

The whole specialisation is the best place to start if you are looking to productionize your machine learning models. The way they put forward each and every concept of MLOps life cycle will be a big eye opener, for people who are taking your machine learning models to production.

I am an experienced MLE and I found this course very useful. However, in the beginning I thought it might be basic concepts, but after finishing the course I still need to go back to take some notes. It improves my skill that I will apply in my current job. Thanks a lot Andrew.

I had a great experience with the content in this course. Some of the valuable tips given by Andrew match some takeaways from my work experiences, but many others were new to me. So, speaking for myself, even for someone already working in the domain, it is a valuable course.

The course goes through error analysis, experiment tracking, scoping and more concepts related to machine learning projects. Very well taught by Andrew Ng.

It is an excellent introductory course to ML projects management in a production framework and has my warm recommendation.

This course is very hands-on. It clearly teaches Machine learning beyond python notebook. I enjoyed this course and currently taking the second part of this specialization "Machine Learning Data Lifecycle in Production". Great content from Andrew Ng and Robert Crowe.

This course is full of practical insights on how to tackle real-world machine learning problems. Specifically for me, I was working on a problem for a long time and after taking this course and applying the skills I learned, I was able to get a wonderful outcome.

It's really refreshing to see the "behind the scenes" perspective on ML algorithm development. Although I have been working in Computer Vision for more than 10 years, I found Andrew's frameworks to think about the project lifecycle and data very useful. Thank you!

This is really one of the most important courses I ever took! Andrew as always explaining in a very clear and interesting way. The course material are so useful, I have been working in the ML field for 2 years and I learned a lot of new concepts in this course.

Great theorical material to understand ML projects. The 1st (ungraded) lab exercise was not very clear though when playing with the front end and back end application, it would be nice to provide more information or tips on how to complete it

Great course, concise but valuable insights on how ML is actually used in the real world and what problems we typically face when deploying ML to solve actual business problems. Looking forward to the upcoming courses in this specialization.

Very compact but covers all the necessary topics. Every Machine Learning Engineer should learn to take his/her ML model to production. This is the course to attend to learn about production deployment of machine learning model-code.

It covers a lot of the real world problems data scientists find when trying to build machine learning solutions. Many of the best practices reviewed here are a common sense thing but having it wrapped toghteter here was really great !

This is an excellent course! Andrew is a great content creator and he has a very pleasant way of presenting and transferring knowledge. I hold him in the highest regard. The tips are very practical and the course is well structured.

Deep learning courses are always best, cover all aspects in theoretical as well as more emphasize on practical knowledge which helps a learner ready for the real life challenges in Data science domain...Thank You Andrew NG and Team

Las explicaciones de Andrew Ng son inmejorables, con un enfoque muy práctico y compartiendo de una forma muy clara sus conocimientos y experiencia. Los recursos de laboratorio y referencias opcionales aportan mucho valor al curso.

This course gives useful insights about deploying machine learning systems in production from PoC stage. These insights are the same that an experienced ML engineer would have got in his/her practical experience in the industry.

Amazing introductory course that gives you the full scope immediately, as well as many theoretical details on each section. I expect the following courses of the specialization to dive into more technical things and frameworks.

Excellent course!! A new way to understand the key factors to master the Machine Learning lifecycle. This is much more than one course, this is an invitation to change our mindset through an exciting journey with Andrew Ng!!

Gives a good overview of MLOps and has extremely practical insights that I wish I knew on past projects or wish I trusted my gut on more. An example of this is the data-centric approach Andrew recommends for modelling.

For someone not starting out with machine learning in production it is a good introduction and for someone with experience it can be good with another perspective on ml in production, just run the videos on 2x speed.

I needed to reset my deadline and start my learning again from week1 but it say error and was unable to reset the deadline. Not happy with the support.

this is not about the course content but support for new users.