AI252 Introduction to Python Programming and to Red Hat OpenShift AI Course Overview

Prerequisites for AI252 Introduction to Python Programming and Red Hat OpenShift AI Course

To ensure you can successfully undertake the AI252 course, the following prerequisites are recommended:

• Basic Experience with Git: Familiarity with version control using Git is required.
• Experience with Red Hat OpenShift: Prior experience is necessary, or you should have completed the Red Hat OpenShift Developer II: Building and Deploying Cloud-native Applications (DO288) course.
• Fundamental Understanding of AI, Data Science, and Machine Learning: Basic experience in these fields is recommended to facilitate better comprehension of the course materials.

These prerequisites are designed to ensure you have the foundational knowledge required to fully benefit from the course and apply the skills learned effectively.

Target Audience for AI252 Introduction to Python Programming and to Red Hat OpenShift AI

1. Introduction
   AI252 is a comprehensive course aimed at equipping professionals with Python programming skills and expertise in managing AI/ML workloads using Red Hat OpenShift AI.

   
   

2. Target Audience and Job Roles

   
   

• System Administrators
• Data Scientists
• Software Developers
• AI/ML Engineers
• DevOps Engineers
• Cloud Developers
• IT Professionals looking to upskill in AI/ML
• Red Hat OpenShift Administrators
• Technical Leads
• Research Analysts
• Python Beginners with basic AI knowledge
• Professionals working on AI/ML model deployment

Learning Objectives - What you will Learn in this AI252 Introduction to Python Programming and to Red Hat OpenShift AI?

Introduction

The AI252 course provides a comprehensive introduction to Python programming and managing AI/ML workloads using Red Hat OpenShift AI. Students will gain foundational skills in Python and practical experience with Red Hat OpenShift AI, enabling them to handle AI/ML projects efficiently.

Learning Objectives and Outcomes

• Understand the fundamentals of Python 3 and set up the developer environment.
• Learn and apply basic Python syntax and semantics.
• Utilize control flow features and operators to write efficient Python code.
• Manipulate compound data using lists, sets, tuples, and dictionaries.
• Develop modular code with functions and modules for flexibility and reuse.
• Explore Object-Oriented Programming (OOP) with classes and objects.
• Handle runtime errors effectively using exceptions.
• Implement file I/O operations for reading and writing files.
• Use advanced data structures like generators and comprehensions to reduce boilerplate code.
• Parse JSON data for efficient data exchange.
• Debug Python programs using the Python debugger (pdb).
• Identify the features and architecture of Red Hat OpenShift AI.
• Organize AI/ML projects using data science projects, workbenches, and data connections.
• Use Jupyter notebooks to execute and test code interactively.