Course information

Kubeflow Training Course Outline

Module 1: Getting Started

  • Introduction
  • Architecture
  • Installing Kubeflow

Module 2: Central Dashboard

  • Introduction to Central Dashboard
  • Customizing Menu Items
  • Registration Flow

Module 3: Kubeflow Notebooks

  • Overview
  • Container Images
  • Submit Kubernetes Resources
  • Troubleshooting
  • Kubeflow Notebooks API

Module 4: Kubeflow Pipelines

  • Introduction
  • Overview
  • Concepts Used in Pipelines
  • Installation
  • Pipelines SDK
  • Pipelines SDK (v2)
  • Troubleshooting

Module 5: Katib

  • Introduction to Katib
  • Getting Started with Katib
  • Running an Experiment
  • Overview of Trial Templates
  • Using Early Stopping
  • Katib Configuration Overview
  • Environment Variables for Katib Components

Module 6: Multi-Tenancy

  • Introduction to Multi-User Isolation
  • Design for Multi-User Isolation
  • Getting Started with Multi-User Isolation

Module 7: External Add-Ons

  • Elyra
  • Istio
  • Kale
  • KServe
  • Migration
  • Models UI
  • Run Your First InferenceService
  • Fairing
  • Overview of Kubeflow Fairing
  • Install Kubeflow Fairing
  • Configure Kubeflow Fairing
  • Fairing on Azure and GCP
  • Feature Store
  • Introduction to Feast
  • Getting Started with Feast
  • Tools for Serving
  • Seldon Core Serving
  • BentoML
  • MLRun Serving Pipelines
  • NVIDIA Triton Inference Server
  • TensorFlow Serving
  • TensorFlow Batch Prediction

Module 8: Kubeflow Distributions

  • Kubeflow on AWS
  • Arrikto Enterprise Kubeflow
  • Arrikto Kubeflow as a Service
  • Charmed Kubeflow

Module 9: Kubeflow on Azure

  • Deployment
  • Authentication Using OIDC in Azure
  • Azure Machine Learning Components
  • Access Control for Azure Deployment
  • Configure Azure MySQL Database to Store Metadata
  • Troubleshooting Deployments on Azure AKS

Module 10: Kubeflow on Google Cloud

  • Deployment
  • Pipelines on Google Cloud
  • Customize Kubeflow on GKE
  • Using Your Own Domain
  • Authenticating Kubeflow to Google Cloud
  • Securing Your Clusters
  • Troubleshooting Deployments on GKE
  • Kubeflow On-Premises on Anthos

Module 11: Kubeflow on IBM Cloud

  • Create or Access an IBM Cloud Kubernetes Cluster
  • Create or Access an IBM Cloud Kubernetes Cluster on a VPC
  • Kubeflow Deployment on IBM Cloud
  • Pipelines on IBM Cloud Kubernetes Service (IKS)
  • Using IBM Cloud Container Registry (ICR)
  • End-to-End Kubeflow on IBM Cloud

Module 12: Kubeflow on Nutanix Karbon

  • Install Kubeflow on Nutanix Karbon
  • Integrate with Nutanix Storage
  • Uninstall Kubeflow

Module 13: Kubeflow Operator

  • Introduction to Kubeflow Operator
  • Installing Kubeflow Operator
  • Installing Kubeflow
  • Uninstalling Kubeflow
  • Uninstalling Kubeflow Operator
  • Troubleshooting

Module 14: Kubeflow on OpenShift

  • Install Kubeflow on OpenShift
  • Uninstall Kubeflow

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Who should attend this Kubeflow Training Course?

The Kubeflow Course in Seattle is designed for those who want to get better at streamlining their Machine Learning Workflows via Kubeflow, an open-source Machine Learning platform. This course can be beneficial to variety of professionals, including:

  • Data Scientists
  • Software Developers
  • Data Analysts
  • Data Engineers
  • DevOps Engineers
  • Cloud Engineers
  • AI and ML Experts 

Prerequisites of the Kubeflow Training Course

There are no formal prerequisites for this Kubeflow Course.

Kubeflow Training Course Overview

Kubeflow is an essential platform for orchestrating and deploying Machine Learning (ML) and data science workflows on Kubernetes. In the rapidly evolving field of DevOps, mastering Kubeflow is crucial. Kubeflow streamlines the deployment of ML models, making it pertinent for DevOps professionals looking to enhance their skills in ML operations. This course in Seattle equips learners with the knowledge to excel in DevOps by integrating Machine Learning seamlessly.

Proficiency in Kubeflow is imperative for DevOps professionals aiming to excel in their careers. It empowers them to manage complex ML pipelines efficiently, ensuring the seamless integration of ML models into their applications. This DevOps Certification Training in Seattle is tailored for DevOps Practitioners, Data Engineers, and anyone seeking DevOps Certifications, as it equips them with the skills needed to navigate the increasingly data-driven world of DevOps.

In this 2-day Kubeflow Training offered by The Knowledge Academy in Seattle, delegates will gain a deep understanding of Kubeflow and the development of Machine Learning pipelines. During this DevOps Certification, delegates will learn about the architecture and installation process of Kubeflow. Our highly professional instructors with years of experience in teaching technical DevOps Courses will conduct this training course.

Course Objectives:

  • To deploy Machine Learning systems to several environments for development
  • To evaluate the output of many stages of the Machine Learning workflow
  • To use Jupyter and TensorFlow in Kubeflow Notebooks effectively
  • To set up Kubeflow with authentication and authorization support through OIDC in Azure
  • To identify the problems and collect data to train the Machine Learning model
  • To evaluate the output of various stages and apply changes to the model

After completing this DevOps Certification Course in Seattle, delegates will be equipped with the knowledge and skills needed to excel in DevOps roles requiring ML integration. This course serves as a solid foundation for those pursuing DevOps Certification, helping them stand out in the competitive field of DevOps.

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What’s included in this Kubeflow Training Course?

  • World-Class Training Sessions from Experienced Instructors
  • Kubeflow Certificate
  • Digital Delegate Pack

Why choose us

Our Seattle venue

Includes..

Free Wi-Fi

To make sure you’re always connected we offer completely free and easy to access wi-fi.

Air conditioned

To keep you comfortable during your course we offer a fully air conditioned environment.

Full IT support

IT support is on hand to sort out any unforseen issues that may arise.

Video equipment

This location has full video conferencing equipment.

Seattle is a West Coast city in America. Seattle has around 667,000 residents and is the largest city in the state of Washington and in the Pacific Northwest region of North America. The metropolitan area of Seattle has around 3.6 million residents. Seattle had a notable music scene between the 20’s and 50’s producing early careers for Ray Charles and Quincy Jones. Seattle is home to the University of Washington which was established in 1861. The University of Washington is a public research university and features one of the most notable medical schools in the world. The University of Washington has around 45,000 students and offers 140 departments with studies in courses such as; Arts and Science, Dentistry, Education, Engineering, Law, Medicine, Nursing, Pharmacy and Public Health. The University has a large sports department, and offers scholarships and opportunities in sports such as; Football, Soccer, Basketball, Softball and Rowing which is a long standing traditional at the University. The University of Washington Educational Outreach is another institute located in Seattle. The University was established in 1912. The University offers various different programs, classes and workshops in studies such as communication, English, Humanities, Social Sciences, Health Informatics and Health Information Management. Seattle is also the home to a number of smaller universities including Seattle University is a catholic university in Seattle that was established in 1891. Seattle University has over 7,500 students and offers courses in Business & Economics, Arts & Sciences, Humanities, Teaching, Nursing, Engineering, Theology and Law. Seattle Pacific University is another University situated in Seattle. This University was established in 1913 and is a Christian University. The Seattle Pacific University has around 4,000 students in attendance. The University offers courses in Fine Arts, Humanities, Science, Engineering, Social & Behavioural Sciences, Business, Education, Health, Psychology and Theology. Some notable alumni attended Seattle Pacific University like David T. Wong who was the co-inventor of Prozac and Dan Price who is the CEO of Gravity Payments. 

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Address

Silver Cloud Inn Lake Union
1150 Fairview Ave North
Seattle
Washington
98109

T: +1 7204454674

Ways to take this course

Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Kubeflow Training | DevOps in Seattle. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.

Unlock your potential with The Knowledge Academy's Kubeflow Training | DevOps in Seattle, accessible anytime, anywhere on any device. Enjoy 90 days of online course access, extendable upon request, and benefit from the support of our expert trainers. Elevate your skills at your own pace with our Online Self-paced sessions.

Streamline large-scale training requirements with The Knowledge Academy's In-house/Onsite at your business premises. Experience expert-led classroom learning from the comfort of your workplace and engage professional development.

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Team building opportunity

Our offers a unique chance for your team to bond and engage in discussions, enriching the learning experience beyond traditional classroom settings

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What our customers are saying

Kubeflow Training | DevOps in Seattle FAQs

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The training fees for certification in Seattle starts from $2295
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Resources are included for a comprehensive learning experience.

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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

Joshua Davies, Thames Water

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