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.
Este curso faz parte do Certificado Profissional Preparação para certificação do Google Cloud: engenheiro de aprendizagem automática
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Informações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 15 horas para completar
Inglês
Legendas: Inglês
O que você vai aprender
Identify and use core technologies required to support effective MLOps.
Configure and provision Google Cloud architectures for reliable and effective MLOps environments.
Adopt the best CI/CD practices in the context of ML systems.
Implement reliable and repeatable training and inference workflows.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 15 horas para completar
Inglês
Legendas: Inglês
oferecido por
Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Programa - O que você aprenderá com este curso
13 minutos para concluir
Welcome to MLOps Fundamentals
This module provides the overview of the course
13 minutos para concluir
1 vídeo (Total 1 mín.), 2 leituras
25 minutos para concluir
Why and When do we need MLOps
In this module, we take a look at machine learning from an operations perspective. This means taking a whole-system view: from defining the problem to the solution.
25 minutos para concluir
3 vídeos (Total 15 mín.)
7 horas para concluir
Understanding the Main Kubernetes Components (Optional)
7 horas para concluir
26 vídeos (Total 106 mín.)
2 horas para concluir
Introduction to AI Platform Pipelines
In this module, we’ll be discussing a Google Cloud product, AI Platform Pipelines, that makes MLOps easy, seamless, and scalable with Google Cloud Services.
2 horas para concluir
6 vídeos (Total 41 mín.)
3 horas para concluir
Training, Tuning and Serving on AI Platform
In this module, we will learn how to train, tune, and serve a model manually from the Jupyter notebook on AI Platform.
3 horas para concluir
8 vídeos (Total 82 mín.)
2 horas para concluir
Kubeflow Pipelines on AI Platform
In this module, we will automate the training and tuning process we described before using a Kubeflow pipeline. Instead of having to trigger every single step of the process manually from the Jupyterlab notebook, we can trigger the entire process with a single click after we have expressed the various steps as a Kubeflow pipeline.
2 horas para concluir
8 vídeos (Total 71 mín.)
1 hora para concluir
CI/CD for Kubeflow Pipelines on AI Platform
In this module, we will be talking about CI/CD for Kubeflow pipelines. We know how to build an automated Kubeflow pipeline, but how can we integrate this pipeline in a continuous integration stack? The goal is to rebuild pipeline assets immediately when new training code is pushed to the corresponding repository.
1 hora para concluir
5 vídeos (Total 13 mín.)
2 minutos para concluir
Summary
This module is a recap of what was covered in the course
2 minutos para concluir
1 vídeo (Total 2 mín.)
Avaliações
- 5 stars47,45%
- 4 stars26,27%
- 3 stars15,53%
- 2 stars4,80%
- 1 star5,93%
Principais avaliações do MLOPS (MACHINE LEARNING OPERATIONS) FUNDAMENTALS
por CS30 de jan de 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.\n\nThankYou So much.
por MS11 de fev de 2022
Videos are good, a lab was initially broken but fixed in a few days.
por DB29 de jan de 2021
excellent experience. thank you very much coursera and google to give the oppurtunity to get certificate free.
por AK20 de fev de 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.
Sobre Certificado Profissional Preparação para certificação do Google Cloud: engenheiro de aprendizagem automática
87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Machine Learning Engineer certification.
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