Red Hat OpenStack Technical Overview

Red Hat OpenShift AI (AI267) equips the learners with the necessary skills required to develop, train, and deploy AI/ML models using Red Hat OpenShift AI. This hands-on course introduces the basic principles of cloud computing, focusing on how the cloud environment can scale and optimise the AI/ML workflows. Students will gain practical experience in establishing and managing the OpenShift environment to suit data science applications.

The course includes major concepts such as Red Hat OpenStack Deployment, providing a strong infrastructure for AI/ML development. Participants will learn how to streamline the workflows using equipment such as Google notebooks and Python, integrate container technologies, and deploy machine learning models in production. The course also emphasises the importance of monitoring capabilities to ensure smooth operation in the production environment.

Ideal for developers and data scientists, this course provides a deep dive into applying AI/ML solutions on cloud platforms. By the end of the course, the learner will be equipped with expertise to effectively manage the AI/ML projects, deploy machine learning models on a scale, and take advantage of the power of Red Hat OpenShift AI for real-world applications.

 


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Learning Options for You

  • Live Training (Duration : 8 Hours)
  • Per Participant

Fee: On Request

Course Prerequisites

Participants should have a solid understanding of basic data science workflows, including knowledge of Python and popular ML frameworks, as well as some familiarity with containers and Kubernetes concepts. This background will enable them to fully benefit from the hands-on, platform-focused skills taught in this program. 

  • Basic understanding of data science and machine learning fundamentals 
  • Familiarity with Python programming 
  • Awareness of container technologies (e.g., Docker) 
  • Introductory knowledge of Kubernetes or OpenShift (recommended but not mandatory) 

Learning Objectives

This course aims to empower participants with the skills needed to develop, deploy, and manage AI/ML applications using Red Hat OpenShift AI. Learners will explore the capabilities of OpenShift as a robust MLOps platform, from managing data science workflows to containerising and scaling AI models. By the end of the course, participants will be able to design end-to-end pipelines, ensure model reproducibility, and streamline the delivery of AI-driven solutions with enterprise-grade security and governance. 

Target Audience

  • Data scientists and machine learning engineers 
  • AI application developers 
  • DevOps engineers working with AI/ML pipelines 
  • Platform engineers managing containerised AI workloads 
  • IT professionals seeking to operationalise AI/ML solutions 
  • Anyone interested in building and deploying ML models at scale on OpenShift 

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