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

Price
$4,400.00 USD

Duration
5 Days

 

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

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

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 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
  • 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

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
  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

Course Prerequisites

Agenda

1 - Basic Python Syntax

  • Explore the basic syntax and semantics of Python

2 - Language Components

  • Understand the basic control flow features and operators

3 - Collections

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

4 - Functions

  • Decompose your programs into composable functions

5 - Modules

  • Organize your code using Modules for flexibility and reuse

6 - Classes in Python

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

7 - Exceptions

  • Handle runtime errors using Exceptions

8 - Input and Output

  • Implement programs that read and write files

9 - Data Structures

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

10 - Parsing JSON

  • Read and write JSON data

11 - Debugging

  • Debug Python programs using the Python debugger (pdb)

12 - Introduction to Machine Learning

  • Describe basic machine learning concepts, different types of machine learning, and machine learning workflows

13 - Training Models

  • Train models by using default and custom workbenches

14 - Enhancing Model Training with RHOAI

  • Use RHOAI to apply best practices in machine learning and data science
 

Get in touch to schedule training for your team
We can enroll multiple students in an upcoming class or schedule a dedicated private training event designed to meet your organization’s needs.

 



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