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AI067 Red Hat OpenShift AI Technical Overview Course Overview

AI067 Red Hat OpenShift AI Technical Overview Course Overview

Discover the AI067 Red Hat OpenShift AI Technical Overview course, a free technical overview designed to enhance your understanding of the AI/ML landscape. This course explores the challenges of developing and deploying AI/ML applications, focusing on how Red Hat OpenShift AI leverages Red Hat OpenShift for a unified, enterprise-ready hybrid AI and MLOps platform.

Audience:
- Data scientists and AI practitioners
- Developers integrating AI/ML
- MLOps Engineers managing AI/ML applications

Learning Objectives:
- Grasp the history and evolution of AI/ML.
- Understand machine learning and deep learning.
- Learn about foundational models within AI.
- Explore Red Hat OpenShift AI's architecture and ecosystem.
- Gain practical insights through hands-on demos.

Enhance your skills and operationalize AI effectively with Red Hat OpenShift AI.

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Course Prerequisites

Prerequisites for AI067 Red Hat OpenShift AI Technical Overview

To successfully undertake the AI067 Red Hat OpenShift AI Technical Overview course, we recommend the following minimum prerequisites:


  • Basic Understanding of Machine Learning Concepts: Familiarity with fundamental machine learning concepts and terminologies.
  • Experience with AI/ML Tools: Prior hands-on experience with AI/ML tools or frameworks.
  • Basic Knowledge of Software Development: Understanding basic software development principles and experience with programming languages.
  • Familiarity with Containerization: Basic knowledge of containerization technologies like Docker and Kubernetes is beneficial but not mandatory.

These prerequisites are designed to ensure you have a foundational understanding that will help you get the most out of the course. Don't worry if you don't meet all of them perfectly; the course is structured to provide a comprehensive overview that will be beneficial regardless of your starting point.


DO080 - Containers, Kubernetes and Red Hat OpenShift Technical Overview
AI067 Red Hat OpenShift AI Technical Overview
Developing and Deploying AI/ML Applications on Red Hat OpenShift AI (AI267)

Target Audience for AI067 Red Hat OpenShift AI Technical Overview

Red Hat OpenShift AI Technical Overview (AI067) is a free course designed for professionals interested in understanding the AI/ML landscape and leveraging Red Hat OpenShift AI for enterprise-ready AI and MLOps solutions.


  • Data Scientists
  • AI Practitioners
  • Developers
  • MLOps Engineers
  • Software Engineers
  • IT Managers
  • System Architects
  • Cloud Engineers
  • DevOps Engineers
  • Research Scientists
  • AI/ML Project Managers
  • Technical Consultants


Learning Objectives - What you will Learn in this AI067 Red Hat OpenShift AI Technical Overview?

Learning Objectives and Outcomes for AI067 Red Hat OpenShift AI Technical Overview

Introduction

The AI067 Red Hat OpenShift AI Technical Overview course offers an in-depth look at the AI/ML landscape and details the integration, operationalization, and deployment of AI/ML applications using Red Hat OpenShift AI.

Learning Objectives and Outcomes

By the end of this course, you will be able to:

  • Understand the AI/ML Landscape: Gain insights into the current state and evolution of AI and machine learning technologies.
  • Identify Key AI Concepts: Learn about machine learning, deep learning, and where foundational models fit within the AI ecosystem.
  • Recognize MLOps Challenges: Understand the difficulties involved in managing machine learning operations (MLOps) and how to overcome them.
  • Operationalize AI/ML: Learn the steps to operationalize AI applications using Red Hat OpenShift AI.
  • Explore Red Hat OpenShift AI Features: Get acquainted with key features and components of Red Hat OpenShift AI.
  • Understand Open Source Ecosystem: Dive into the open source ecosystem that supports Red Hat OpenShift AI.
  • Analyze Red Hat OpenShift AI Architecture: Understand the architectural framework of Red Hat OpenShift AI.
  • **Leverage Partner

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