返回到 Machine Learning Operations (MLOps): Getting Started
Google Cloud

Machine Learning Operations (MLOps): Getting Started

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 <<<

状态:Google Cloud Platform
状态:Data Pipelines
中级课程小时

精选评论

RL

4.0评论日期:Jan 5, 2022

I​t's ok. There are example notebooks to understand the code. The pricing part is missing.

SC

5.0评论日期:Jul 6, 2021

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

DM

5.0评论日期:Feb 1, 2021

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

PA

5.0评论日期:Feb 22, 2021

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

SR

4.0评论日期:Feb 14, 2021

It is a good designed course, but I would prefer to have basic knowledge of Machine learning and data science in order to understand this course even much better.

EC

5.0评论日期:Dec 5, 2024

Some of the instructions in the Lab need to be updated. Great course!!!

JM

4.0评论日期:Dec 31, 2020

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.

JS

4.0评论日期:Jul 16, 2023

Good starter on basic MLOps on GCP for those who want a quick dive and a hands on project

AK

4.0评论日期:Feb 20, 2021

Loved the content, labs, and regularly intervened quiz. The only suggestion is that, for Juniper Labs, a detailed video solution would have added more value to this course.

AM

5.0评论日期: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.

DB

5.0评论日期:Jan 29, 2021

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

CS

4.0评论日期:Jan 30, 2021

I think there should be more content about AIML can be better choice or preferable.Otherwise all the things are okay I enjoyed this course and learn a lot.ThankYou So much.

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显示:20/127

Ruhua Jiang
2.0
评论日期:Dec 8, 2020
Satrio Wicara Putra
1.0
评论日期:Dec 17, 2020
Arthur Jochems
2.0
评论日期:Dec 8, 2020
Joana Matos
2.0
评论日期:Jan 4, 2021
Kshitiz Rimal
1.0
评论日期:Dec 30, 2020
Hugo Perrier
3.0
评论日期:Dec 31, 2020
Jon Maurer
4.0
评论日期:Jan 1, 2021
Peng Lee
4.0
评论日期:Dec 12, 2020
nerisha s
1.0
评论日期:Nov 30, 2020
Artur Yakimovich
1.0
评论日期:Jan 11, 2021
Tarun Kumar
5.0
评论日期:Feb 19, 2021
Surachart Opun
5.0
评论日期:Nov 12, 2020
Dmitriy
5.0
评论日期:Dec 10, 2020
Walter Hoekstra
3.0
评论日期:Sep 8, 2021
João Fábio Scurçoni
1.0
评论日期:Jul 30, 2022
Rob L'Heureux
1.0
评论日期:Oct 21, 2023
zeroone_ai
1.0
评论日期:Apr 28, 2021
Priyanka Avhad
5.0
评论日期:Feb 23, 2021
Anshumaan Kumar Prasad
4.0
评论日期:Jan 16, 2021
Yağızhan Arslan Akıncı
2.0
评论日期:Feb 7, 2022