Creating Machine Learning Models with Python and Red Hat OpenShift AI (AI253)

 

Course Overview

An introduction to Python programming, to machine learning concepts, and how to use Red Hat OpenShift AI to train ML models.

Moyens Pédagogiques :
  • Quiz pré-formation de vérification des connaissances (si applicable)
  • Réalisation de la formation par un formateur agréé par l’éditeur
  • Formation réalisable en présentiel ou en distanciel
  • Mise à disposition de labs distants/plateforme de lab pour chacun des participants (si applicable à la formation)
  • Distribution de supports de cours officiels en langue anglaise pour chacun des participants
    • Il est nécessaire d'avoir une connaissance de l'anglais technique écrit pour la compréhension des supports de cours
Moyens d'évaluation :
  • Quiz pré-formation de vérification des connaissances (si applicable)
  • Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
  • Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences

Who should attend

  • 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
  • MLOps engineers responsible for installing, configuring, deploying, and monitoring AI/ML applications on Red Hat OpenShift AI

Prerequisites

Course Objectives

Impact on the Organization

Organizations collect and store vast amounts of information from multiple sources. With Red Hat OpenShift AI, organizations have a platform ready to analyze data, visualize trends and patterns, and predict future business outcomes by using machine learning and artificial intelligence algorithms.

Impact on the Individual

As a result of attending this course, you will understand the foundations of the Red Hat OpenShift AI architecture. You will be able to organize code and configuration by using data science projects, workbenches, and data connections. You will also be able to execute and test code interactively by using Jupyter notebooks. This course is the starting point for the AI/ML learning path in which you will learn how to create and maintain AI/ML workflows.

Course Content

Python is a popular programming language used by system administrators, data scientists, and developers to create applications, perform statistical analysis, and train AI/ML models. This course introduces the Python language and teaches students basic machine learning concepts, and the different types of machine learning. This course helps students build core skills such as using Red Hat OpenShift AI to train ML models and how to apply best practices when training models through hands-on experience.

This course is based on Python 3, RHEL 9.0, Red Hat OpenShift ® 4.14, and Red Hat OpenShift AI 2.8.

Course Content Summary

  • Basics of Python syntax, functions and data types
  • How to debug Python scripts using the Python debugger (pdb)
  • Use Python data structures like dictionaries, sets, tuples and lists to handle compound data
  • Learn Object-oriented programming in Python and Exception Handling
  • How to read and write files in Python and parse JSON data
  • Use powerful regular expressions in Python to manipulate text
  • How to effectively structure large Python programs using modules and namespaces
  • Introduction to Machine Learning
  • Training Models
  • Enhancing Model Training with RHOAI

Prix & Delivery methods

Formation en ligne

Durée
5 jours

Prix
  • 3 340,– €
Dates et Inscription
Demande de date
Formation en salle équipée

Durée
4 jours

Prix
  • France : 3 340,– €
Dates et Inscription
Demande de date

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