Os cursos de treinamento ao vivo Kubeflow , ministrados por instrutores do Kubeflow demonstram, através da prática interativa, como usar o Kubeflow para criar, implantar e gerenciar fluxos de trabalho de aprendizado de máquina no Kubernetes . Kubeflow treinamento Kubeflow está disponível como "treinamento ao vivo no local" ou "treinamento ao vivo remoto". O treinamento ao vivo no local pode ser realizado localmente nas instalações do cliente em Portugal ou nos centros de treinamento corporativo NobleProg em Portugal . O treinamento remoto ao vivo é realizado por meio de uma área de trabalho remota interativa. NobleProg - Seu provedor de treinamento local
Machine Translated
Declaração de Clientes
The exercise VMs were working quite well.
Philippe DEPRUGNEY - Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
Resources preparation (VMs and such) and the ability to answer questions
Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
Kamil's pleasant way backed by his knowledge on the subject matter was the best part of this course
Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
The trainer was extremely approachable and helpful and was able to solve any issues that we encountered in the class. Even after he had finished all of the planned course material he still stayed on late to answer questions some people in the course had.
Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
The hands on exercises
Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
Kamil nos trouxe de novatos no Docker e Kubernetes a usuários confiantes (se não PME!) Em apenas três dias. Ele sempre foi acessível e paciente ao responder minhas perguntas. Um verdadeiro gent.
Patrick Kennedy - Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
Machine Translated
Exercises, practical questions answered clearly
Mayeul Marguet - Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
Go mistura de exercícios práticos e teoria, Kamil deu um treinamento bem focado, adaptado às nossas necessidades, mesmo que o conteúdo do curso seja muito amplo por 3 dias.
Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
Machine Translated
The subject, and trainer knowledge
Thiqha Business Services
Curso: Docker, Kubernetes e OpenShift para Desenvolvedores e Administradores
Que Brian tem um bom conhecimento do assunto e explica bem
Francisco Demetrio Quitral - IMED S.A
Curso: Managing Kubernetes with Rancher
Machine Translated
que nos foi mostrado como os comandos do kubectl eram refletidos na interface do rancher e nos serviços da AWS, o que deixou muito claro como as diferentes partes interagem.
IMED S.A
Curso: Managing Kubernetes with Rancher
Machine Translated
The techical knowlegde of the trainer about the subject so he can answer most of the questions.
Synchronoss Software Ireland Limited
Curso: Docker e Kubernetes
The exercises
Van Tonilin Ramos - Temic Automotive Philippines
Curso: Docker e Kubernetes
All
Eduardo Darroca Jr - Temic Automotive Philippines
Curso: Docker e Kubernetes
It never felt like the pace was high but we still managed to cover many topics in only three days. I liked that Adriano did not stop the lecture to have us do labs. The style of trying out commands in the lab environment while watching and listening to the lecture was good in my opinion. Adriano was very flexible to answer questions that came up without getting distracted too much from the current topic.
Bolagsverket
Curso: Docker e Kubernetes
todos
Mikael Larsson Österström - Bolagsverket
Curso: Docker e Kubernetes
Machine Translated
The teacher has worked with the subject
Bolagsverket
Curso: Docker e Kubernetes
The material in general. The trainer was very knowledgable.
MDA Systems Ltd.
Curso: Kubernetes Advanced
A maneira do treinador de explicar o assunto e de quem tornar o conceito muito simples.
Faten AlDawish - TAMKEEN TECHNOLOGIES COMPANY
Curso: Docker and Kubernetes: Building and Scaling a Containerized Application
Machine Translated
laboratórios e esclarecimento de dúvidas
venkata velpuri - Charter Communications INC
Curso: Kubernetes from Basic to Advanced
Machine Translated
Treinamento prático.
Charter Communications INC
Curso: Kubernetes from Basic to Advanced
Machine Translated
Não me senti entediado durante a sessão de treinamento.
Charter Communications INC
Curso: Kubernetes from Basic to Advanced
Machine Translated
Fantastic delivery of the training, really enjoyable and all round good vibe throughout
Chris Brant - Hewlett Packard Enterprise
Curso: Docker e Kubernetes
Gostei dos exemplos que complementavam a teoria na apresentação.
Miłosz Gałązka - LPP S.A.
Curso: OpenShift para Administradores
Machine Translated
We did small examples. I have seen a lot of huge config files and they always looked overwhelming. It was really nice to see small examples!
Marcus Nordberg - TriOptima AB
Curso: Docker e Kubernetes
Kamil's attitude and knowledge. Very friendly, highly knowledgeable about the subject, great listener.
TriOptima AB
Curso: Docker e Kubernetes
Kamil's expertise and patience while guiding me through some complex topics. His ability to spontaneously answer some difficult questions that I had about the material. I'd give him an A++.
Curso: Docker e Kubernetes
the intro and the structure of the slides
Abraxas Informatik AG
Curso: Managing Kubernetes with Rancher
Kamil's expertise and patience while guiding me through some complex topics. His ability to spontaneously answer some difficult questions that I had about the material. I'd give him an A++.
Curso: Docker e Kubernetes
Programa de curso Kubeflow
Nome do Curso
Duração
Visão geral
Nome do Curso
Duração
Visão geral
35 horas
Visão geral
Kubeflow is a toolkit for making Machine Learning (ML) on Kubernetes easy, portable and scalable. AWS EKS (Elastic Kubernetes Service) is an Amazon managed service for running the Kubernetes on AWS.
This instructor-led, live training (onsite or remote) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.
By the end of this training, participants will be able to:
- Install and configure Kubeflow on premise and in the cloud using AWS EKS (Elastic Kubernetes Service).
- Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
- Run entire machine learning pipelines on diverse architectures and cloud environments.
- Using Kubeflow to spawn and manage Jupyter notebooks.
- Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (onsite or remote) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.
By the end of this training, participants will be able to:
- Install and configure Kubeflow on premise and in the cloud using AWS EKS (Elastic Kubernetes Service).
- Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
- Run entire machine learning pipelines on diverse architectures and cloud environments.
- Using Kubeflow to spawn and manage Jupyter notebooks.
- Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
28 horas
Visão geral
Kubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is a machine learning library and Kubernetes is an orchestration platform for managing containerized applications.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to an AWS EC2 server.
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on AWS.
- Use EKS (Elastic Kubernetes Service) to simplify the work of initializing a Kubernetes cluster on AWS.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other AWS managed services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to an AWS EC2 server.
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on AWS.
- Use EKS (Elastic Kubernetes Service) to simplify the work of initializing a Kubernetes cluster on AWS.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other AWS managed services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
28 horas
Visão geral
Kubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is one of the most popular machine learning libraries. Kubernetes is an orchestration platform for managing containerized applications.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to Azure cloud.
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on Azure.
- Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other AWS managed services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to Azure cloud.
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on Azure.
- Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other AWS managed services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
28 horas
Visão geral
Kubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is one of the most popular machine learning libraries. Kubernetes is an orchestration platform for managing containerized applications.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to Google Cloud Platform (GCP).
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on GCP and GKE.
- Use GKE (Kubernetes Kubernetes Engine) to simplify the work of initializing a Kubernetes cluster on GCP.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other GCP services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to Google Cloud Platform (GCP).
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on GCP and GKE.
- Use GKE (Kubernetes Kubernetes Engine) to simplify the work of initializing a Kubernetes cluster on GCP.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other GCP services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
28 horas
Visão geral
Kubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is one of the most popular machine learning libraries. Kubernetes is an orchestration platform for managing containerized applications.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to IBM Cloud Kubernetes Service (IKS).
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on IBM Cloud Kubernetes Service (IKS).
- Use IKS to simplify the work of initializing a Kubernetes cluster on IBM Cloud.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other IBM Cloud services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to IBM Cloud Kubernetes Service (IKS).
By the end of this training, participants will be able to:
- Install and configure Kubernetes, Kubeflow and other needed software on IBM Cloud Kubernetes Service (IKS).
- Use IKS to simplify the work of initializing a Kubernetes cluster on IBM Cloud.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Leverage other IBM Cloud services to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
28 horas
Visão geral
Kubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is one of the most popular machine learning libraries. Kubernetes is an orchestration platform for managing containerized applications. OpenShift is an cloud application development platform that uses Docker containers, orchestrated and managed by Kubernetes, on a foundation of Red Hat Enterprise Linux.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to an OpenShift on-premise or hybrid cloud.
- By the end of this training, participants will be able to:
- Install and configure Kubernetes and Kubeflow on an OpenShift cluster.
- Use OpenShift to simplify the work of initializing a Kubernetes cluster.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Call public cloud services (e.g., AWS services) from within OpenShift to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (onsite or remote) is aimed at engineers who wish to deploy Machine Learning workloads to an OpenShift on-premise or hybrid cloud.
- By the end of this training, participants will be able to:
- Install and configure Kubernetes and Kubeflow on an OpenShift cluster.
- Use OpenShift to simplify the work of initializing a Kubernetes cluster.
- Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
- Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
- Call public cloud services (e.g., AWS services) from within OpenShift to extend an ML application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
28 horas
Visão geral
Kubeflow is a toolkit for making Machine Learning (ML) on Kubernetes easy, portable and scalable.
This instructor-led, live training (onsite or remote) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.
By the end of this training, participants will be able to:
- Install and configure Kubeflow on premise and in the cloud.
- Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
- Run entire machine learning pipelines on diverse architectures and cloud environments.
- Using Kubeflow to spawn and manage Jupyter notebooks.
- Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
- To learn more about Kubeflow, please visit: https://github.com/kubeflow/kubeflow
This instructor-led, live training (onsite or remote) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.
By the end of this training, participants will be able to:
- Install and configure Kubeflow on premise and in the cloud.
- Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
- Run entire machine learning pipelines on diverse architectures and cloud environments.
- Using Kubeflow to spawn and manage Jupyter notebooks.
- Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
- To learn more about Kubeflow, please visit: https://github.com/kubeflow/kubeflow
Próximos Cursos de Kubeflow
2020-06-22 09:30:00
Lisbon Airport Business Center
28 horas
2020-08-03 09:30:00
Porto
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2020-08-12 09:30:00
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28 horas
2020-10-05 09:30:00
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2020-11-30 09:30:00
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28 horas
Consultoria
Cursos de fim de semana de Kubeflow, Treinamento tardiurno de Kubeflow, Treinamento em grupo de Kubeflow, Kubeflow guiado por instrutor, Treinamento de Kubeflow de fim de semana, Cursos de Kubeflow tardiurnos, coaching de Kubeflow, Instrutor de Kubeflow, Treinador de Kubeflow, Cursos de treinamento de Kubeflow, Aulas de Kubeflow, Kubeflow no local do cliente, Cursos privados de Kubeflow, Treinamento individual de Kubeflow
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