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AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam Course Overview

AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam Course Overview

## Overview of AI268: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam

AI268 is a comprehensive course designed to introduce participants to the development and deployment of AI/ML applications on Red Hat OpenShift AI. Through hands-on experience, students will learn core skills for training, developing, and deploying machine learning models using OpenShift AI.

Key learning objectives include understanding the architecture and components of Red Hat OpenShift AI, utilizing Jupyter notebooks for interactive testing, and creating custom notebook images. Practical applications cover installing and managing OpenShift AI, training models, and serving machine learning models. Additionally, students will explore data science pipelines using Elyra and Kubeflow Pipelines.

This course is based on Red Hat OpenShift 4.14 and includes the Red Hat Certified Specialist in OpenShift AI Exam (EX267), equipping learners with the expertise needed for real-world AI/ML projects.

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Course Prerequisites

The AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam course requires the following prerequisites to ensure you have the foundational knowledge necessary for success:


  • Experience with Git: Familiarity with version control processes and workflows.
  • Experience in Python Development: Proficiency in Python programming or completion of the Python Programming with Red Hat (AD141) course.
  • Experience with Red Hat OpenShift: Knowledge of using Red Hat OpenShift for deploying applications, or completion of the Red Hat OpenShift Developer II: Building and Deploying Cloud-native Applications (DO288) course.
  • Basic Experience in AI, Data Science, and Machine Learning: An understanding of foundational concepts in AI, data science, and machine learning fields is recommended to maximize your learning experience.

These prerequisites aim to provide a solid foundation, ensuring you are well-prepared for the advanced topics covered in this course.


Target Audience for AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam

  1. Introduction:
    The AI268 course covers developing and deploying AI/ML applications on Red Hat OpenShift AI, ideal for professionals seeking hands-on AI model development and deployment skills.


  2. Job Roles and Audience:


  • AI/ML Developers
  • Data Scientists
  • Machine Learning Engineers
  • DevOps Engineers
  • Cloud Developers
  • Python Developers with an interest in AI
  • IT Professionals experienced in Red Hat OpenShift
  • Software Engineers focusing on cloud-native applications
  • Technical Project Managers in AI/ML projects
  • IT Consultants specializing in AI/ML solutions
  • Red Hat Certification Seekers


Learning Objectives - What you will Learn in this AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam?

Learning Outcomes and Concepts Covered

The AI268 Developing and Deploying AI/ML Applications on Red Hat OpenShift AI with Exam course equips students with essential skills for using Red Hat OpenShift AI to develop, deploy, and manage machine learning models.

Learning Objectives and Outcomes

  • Introduction to Red Hat OpenShift AI:

    • Identify the key features, architecture, and components of Red Hat OpenShift AI.

  • Data Science Projects:

    • Organize code and configurations using data science projects, workbenches, and data connections.

  • Jupyter Notebooks:

    • Use Jupyter notebooks for interactive code execution and testing.

  • Installing Red Hat OpenShift AI:

    • Install Red Hat OpenShift AI through the web console and CLI, and manage its components.

  • Managing Users and Resources:

    • Administer users and allocate resources for workbenches in Red Hat OpenShift AI.

  • Custom Notebook Images:

    • Create and import custom notebook images via the OpenShift AI dashboard.

  • Introduction to Machine Learning:

    • Understand basic machine learning concepts, types, and workflows.

  • Training Models:

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