Introduction to Python Programming and to Red Hat OpenShift AI (AI252)

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Course Overview

An introduction to Python programming, and creating and managing AI/ML workloads with Red Hat OpenShift AI.

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 the basics of using Red Hat OpenShift AI for AI/ML workloads. This course helps students build core skills such as describing the Red Hat OpenShift AI architecture, and organizing, executing and testing AI/ML code through hands-on experience. These skills can be applied in all versions of Red Hat OpenShift AI.

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

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

Course Objectives

    • 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
    • How to effectively structure large Python programs using modules and namespaces
    • Introduction to Red Hat OpenShift AI
    • Data Science Projects
    • Jupyter Notebooks

Course Outline

1 - An Overview of Python 3

  • Introduction to Python and setting up the developer environment

2 - Basic Python Syntax

  • Explore the basic syntax and semantics of Python

3 - Language Components

  • Understand the basic control flow features and operators

4 - Collections

  • Write programs that manipulate compound data using lists, sets, tuples and dictionaries

5 - Functions

  • Decompose your programs into composable functions

6 - Modules

  • Organize your code using Modules for flexibility and reuse

7 - Classes in Python

  • Explore Object Oriented Programming (OOP) with classes and objects

8 - Exceptions

  • Handle runtime errors using Exceptions

9 - Input and Output

  • Implement programs that read and write files

10 - Data Structures

  • Use advanced data structures like generators and comprehensions to reduce boilerplate code

11 - Parsing JSON

  • Read and write JSON data

12 - Debugging

  • Debug Python programs using the Python debugger (pdb)

13 - Introduction to Red Hat OpenShift AI

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

14 - Data Science Projects

  • Organize code and configuration by using data science projects, workbenches, and data connections

15 - Jupyter Notebooks

  • Use Jupyter notebooks to execute and test code interactively

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Class Dates & Times

Class times are listed Central time

This is a 5-day class

Class dates not listed.
Please contact us for available dates and times.