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
I have been involved with deep learning for more than 5 years (in academia), nevertheless learned a lot already. I am very curious about the next courses. Thanks for putting together this course!
创建者 Jungwei F•
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.
创建者 Daniel H G•
Excellent course, you learn about the fundamentals of MLOps. A recommended course if you want to understand the life cycle of a Machine Learning algorithm in production.
创建者 Sadashiv B•
This course is fantastic. Exceptionally well understanding of all the fundamental concepts required. Many issues that one would not have considered are well-covered.
创建者 Ratha P•
A great course that Andrew provided to fill the gap between machine learning/AI in academia (model-centric approach) and industry production (data-centric approach).
创建者 Nikki A•
Very well explained, Andrew Ng does a great job as always summarizing complex subjects in easily digestible lectures. A lot of thought went into this course
创建者 Martin T•
Very useful discussions and views. Great reflections on the value of data in the full ML cycle and the real challenges of putting a ML system in production.
创建者 Sergio M C Z•
I really enjoyed the course as it did provide very practical insights and recommendations of best practices to implement ML models in the real world.
创建者 Megan M•
This course is an excellent overview of the steps required to put ML into production. Andrew's explanations are clear, and his examples are spot on.
创建者 Mario G R•
The course was very enjoyable, the readings and classes give you a basic but concise approach of what it means to bring an ML system to production.
创建者 Aswin G•
Excellent resource material to understand the problems faced when deploying ML models in production and how to handle them at each and every stage,
创建者 Kin L K L•
An excellent high level overview of the lifecycle of machine learning model development and deployment with a focus on business applications.
创建者 Tyler G•
Andrew's insights are gold. He explains with clarity and has the foresight to disseminate the knowledge the community needs when we need it.
创建者 Fernanda P G•
Este curso pode abrir minha mente sobre várias possibilidades em IA, estou ansiosa para o próximo. Obrigada pela oportunidade de aprender.
创建者 Adarsh W•
Excellent course to learn about data-centric approach in Machine Learning. All the ungraded labs were also informative and useful.
创建者 Manas M•
As always, another great course taught by Prof. Andrew. Thank you coursera/deeplearning.ai team for offering such a great course.
创建者 Mahsut D•
This is an axcellent introductory course in MLOps, and also for anyone who is looking for having advanced skills in AI career.
创建者 Wooyong E•
Immensely useful. This course is densely packed with practical tips and provides a great overview of this nascent discipline!
创建者 Rui B•
Years of practical experience condensed in this course. Extremely relevant material for Data Scientists / ML Engineers.
创建者 Kiran K K•
I would like to thank Andrew for his very practical insights in the course. I don't think I could have asked for more.
创建者 Mario L d Á M•
Excellent introduction to MLOps by Andrew Ng. Practical and clear. Love the (ungraded) labs, highly recommendable.
创建者 Yusa L•
The material is really close to the real industrial practice. Amazing reference if doing any ML engineering work.
创建者 Mahsa P•
This course is a wonderful overview of different steps of a machine learning project from scoping to deployment.
创建者 david g•
Even as a Data Scientist, I found this very relevant to define & get a clarity on such frameworks & processess
创建者 Olaf S•
The short videos made it easy to work through it fast. In addition the optional-lab tasks were really awesome.
创建者 Dao M D•
Great course for people who want to get the idea of putting Machine Learning notebooks' code into production!