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Back to Machine Learning Operations (MLOps): Getting Started

Learner Reviews & Feedback for Machine Learning Operations (MLOps): Getting Started by Google Cloud

4.0
stars
413 ratings

About the Course

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models. This course is primarily intended for the following participants: Data Scientists looking to quickly go from machine learning prototype to production to deliver business impact. Software Engineers looking to develop Machine Learning Engineering skills. ML Engineers who want to adopt Google Cloud for their ML production projects. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...

Top reviews

AM

Mar 11, 2021

The whole process of building the Kubeflow pipelines for MLOPs including the configuration part (what does into the Dockerfile, cloud build) has been explained fully.

DM

Feb 1, 2021

Thank You , Coursera & Google, It was great session & learn some practical Aspects & fundamentals of ML. I hope it will help me in the future. Thank You.

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1 - 25 of 113 Reviews for Machine Learning Operations (MLOps): Getting Started

By Ruhua J

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Dec 8, 2020

The content is decent. But the labs are pretty broken, not well designed & maintained

By Satrio W P

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Dec 17, 2020

Qwiklabs does not work!!

By Arthur J

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Dec 8, 2020

There's a few things underwhelming about this course. First, GCP has made MLops very complicated, technical and cumbersome. Since you would need to work with this tech on a regular basis, you really don't want this. Second, the tutorials are mostly challenging due to linux. The tutorials are also buggy and setting up the cloud resources takes a lot of time. Overall, not that happy with this course or the subject mater.

By Joana M

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Jan 4, 2021

The qwiklabs have many issues, and due to the limited amount of tries I was not able to complete the course.

By Kshitiz R

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Dec 30, 2020

By far the worst experience. Videos and explanations are really good but all those goodness are killed by the Qwiklabs experience. Labs are frustrating because they don't simply work, not because you did something wrong. I would like to urge the team behind this course to put some effort and time fixing those labs and answer to the questions raised by the learners in discussion forums. By copy pasting the readymade answer to email qwiklabs support team won't help at all.

By Hugo P

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Dec 31, 2020

The Labs could be improved (bugs and clarity)

By Jon M

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Jan 1, 2021

The content related to MLOps on GCP is quite good. If the labs were improved slightly to remove some of the bugs that are commonly posted in the message boards, this would be a 5 star.

By Peng L

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Dec 12, 2020

Course content was good. However, many of the Qwiklabs had bugs, resulting in not being able to complete the course with a grade of 100%.

By nerisha s

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Nov 30, 2020

Accent is difficult to understand. Speaks to quickly. Cannot read subtitles and course content at the same time.

By Artur Y

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Jan 11, 2021

Some labs are impossible to complete due to incompatibility with github. Github requires verification email.

By Tarun K

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Feb 19, 2021

This was a good course along with google qwiklab which guide you through out the lab which makes a enrolled person a successful learner .

By Surachart O

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Nov 12, 2020

Great course to start for learning about MLOps. However, I hope there will have more videos to explain details on LABs.

By Dmitriy

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Dec 10, 2020

I liked it. Made me realize how much of a pain MLOps really is.

By Priyanka A

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Feb 23, 2021

VERY HELPFUL AND KNOWLEDGE BASED COURSE. THANKS TO ALL THE INTRUCTORS.

By Anshumaan K P

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Jan 16, 2021

Some Labs isn't working properly

By Walter H

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Sep 8, 2021

while this course teaches some useful skills, in particular how to to offload ML workloads to GCP, and introduces Kubeflow well, it doesn't go into enough depth to really let the students master the material. It doesn't help that Kubeflow (and its GCP implementation) are fundamentally fairly complicated technologies that compete with other, more mature (but less specialized) tools like Airflow. All in all, a good starting point, but don't expect to master the material - further study will be required. This course only scratches the surface.

By Yağızhan A A

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Feb 7, 2022

Videos are nice and good for learning new perspectives but there is a huge problem in this course. Labs (required to complete if you want certificate) are bugy and for example i need to wait for one lab problem to be solved if i want my certificate (which is going on for more than 2 weeks as i can see in forums). Overall, good quality videos but unexpectedly very poor technical management.

By Joaquin S

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Aug 2, 2022

Some labs are "unavaibale" in the Quicklabs portal. For example, in one Lab the portal says "Sorry, Using custom containers with AI Platform Training is currently unavailable"

By João F S

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Jul 30, 2022

Finish the course , and need to pay for the certificate .Bad Way for Coursera like goes from EDX .

By zeroone_ai

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Apr 28, 2021

quiklabs always have a trouble when I try this cource..

By Dinesh K R

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Apr 17, 2021

This is one of the best course to start on ML OPS with GCP. The Concepts were explained neatly throughout the course, and i am sure this would really help me to solve the most complex use cases in deploying ML Models. Thanks Google for this wonderful course and many appreciations to Qwiklabs for hands-on. Highly recommended for ML Engineers/ Data Scientist.

By Aparna M

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Mar 12, 2021

The whole process of building the Kubeflow pipelines for MLOPs including the configuration part (what does into the Dockerfile, cloud build) has been explained fully.

By Darshankumar N M

•

Feb 2, 2021

Thank You , Coursera & Google, It was great session & learn some practical Aspects & fundamentals of ML. I hope it will help me in the future. Thank You.

By Shreyas R C

•

Jul 7, 2021

Well designed course with Qwiklabs hands-on experience, awesome learning. Thanks to Google Cloud Team and Coursera

By Dipanjan B

•

Jan 30, 2021

excellent experience. thank you very much coursera and google to give the oppurtunity to get certificate free.