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

Detailed Course Outline

Introduction to Python and setting up the developer environment.

Basic Python Syntax
Explore the basic syntax and semantics of Python

Language Components
Understand the basic control flow features and operators

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

Functions
Decompose your programs into composable functions

Modules
Organize your code using Modules for flexibility and reuse

Classes in Python
Explore Object Oriented Programming (OOP) with classes and objects

Exceptions
Handle runtime errors using Exceptions

Input and Output
Implement programs that read and write files

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

Parsing JSON
Read and write JSON data

Debugging Debug Python programs using the Python debugger (pdb)

Introduction to Machine Learning Describe basic machine learning concepts, different types of machine learning, and machine learning workflows

Training Models Train models by using default and custom workbenches

Enhancing Model Training with RHOAI Use RHOAI to apply best practices in machine learning and data science