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

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.
Course Details

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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.

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

Experience with Git is required Experience in Red Hat OpenShift is required, or completion of the Red Hat OpenShift Developer II: Building Kubernetes Applications (DO288) course Basic experience in the AI, data science, and machine learning fields is recommended

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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