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AI267 - Developing and Deploying AI/ML Applications on Red Hat OpenShift AI

  • Length 4 days
  • Price  $4125 inc GST
Course overview
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Why study this course

Developing and Deploying AI/ML Applications on Red Hat OpenShift AI (AI267) provides students with the fundamental knowledge about using Red Hat OpenShift for developing and deploying AI/ML applications. This course helps students build core skills for using Red Hat OpenShift AI to train, develop and deploy machine learning models through hands-on experience.

This course is based on Red Hat OpenShift 4.16, and Red Hat OpenShift AI 2.13.

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What you’ll learn

As a result of attending this course, you will understand the foundations of the Red Hat OpenShift AI architecture. You will be able to install Red Hat OpenShift AI, manage resource allocations, update components and manage users and their permissions. You will also be able to train, deploy and serve models, including how to use Red Hat OpenShift AI to apply best practices in machine learning and data science. Finally you will be able to define and set up data science pipelines with Red Hat OpenShift AI.


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Red Hat is the leading provider of open source, enterprise IT solutions. Lumify Work is proud to offer clients the ability to attend over 40 official Red Hat training courses through a resell agreement with Red Hat. Maximise the return on your Red Hat technology investment with lab-intensive, Instructor-Led Training run by Red Hat themselves. Alternatively, for those unable to attend training, log in and learn with Red Hat Online Learning.


Who is the course for?

  • Data scientists and AI practitioners who want to use Red Hat OpenShift AI to build and train ML models

  • Developers who want to build and integrate AI/ML enabled applications

  • Developers, data scientists, and AI practitioners who want to automate their ML workflows

  • MLOps engineers responsible for operationalizing the ML lifecycle on Red Hat OpenShift AI


Course subjects

Introduction to Red Hat OpenShift AI
Identify the main features of Red Hat OpenShift AI, and describe the architecture and components of Red Hat AI.

Data Science Projects
Organise code and configuration by using data science projects, workbenches, and data connections.

Jupyter Notebooks
Use Jupyter notebooks to execute and test code interactively.

Red Hat OpenShift AI Installation
Install Red Hat OpenShift AI and manage Red Hat OpenShift AI components.

User and Resource Management
Manage Red Hat OpenShift AI users and allocate resources.

Custom Notebook Images
Create and import custom notebook images in Red Hat OpenShift AI.

Introduction to Machine Learning
Describe basic machine learning concepts, different types of machine learning, and machine learning workflows.

Training Models
Train models by using default and custom workbenches.

Enhancing Model Training with RHOAI
Use RHOAI to apply best practices in machine learning and data science.

Introduction to Model Serving
Describe the concepts and components required to export, share, and serve trained machine learning models.

Model Serving in Red Hat OpenShift AI
Serve trained machine learning models with OpenShift AI.

Introduction to Data Science Pipelines
Define and set up Data Science Pipelines.

Working with Pipelines
Create data science pipelines with the Kubeflow SDK and Elyra.

Controlling Pipelines and Experiments
Configure, monitor, and track pipelines with artifacts, metrics, and experiments.


Prerequisites


THIRD PARTY REGISTRATION

Lumify Work offers certification and training in Enterprise Linux, Ansible, JBoss, OpenShift, OpenStack, and more through our partnership with Red Hat. This arrangement requires Lumify Work to provide your details to Red Hat for course and/or exam registration purposes.


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


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