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.
Note: This course is offered as a 4 day in person class or a 5 day virtual class. Durations may vary based on the delivery. For full course details, scheduling, and pricing, select your location then “get started” on the right hand menu.Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
TARGET AUDIENCE:
• 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 PREREQUISITES:
Recommended training
• Experience with Git is required
• Experience in Red Hat OpenShift is required, or completion of the Red Hat OpenShift Developer II: Building and Deploying Cloud-native Applications (DO288) course
• Basic experience in the AI, data science, and machine learning fields is recommended
Technology considerations
• No ILT classroom will be available
COURSE CONTENT:
An Overview of Python 3
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 Red Hat OpenShift AI
Identify the main features of Red Hat OpenShift AI, and describe the architecture and components of Red Hat OpenShift AI.
Data Science Projects
Organize code and configuration by using data science projects, workbenches, and data connections
Jupyter Notebooks
Use Jupyter notebooks to execute and test code interactively
COURSE OBJECTIVE:
• 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
FOLLOW ON COURSES:
Red Hat OpenShift AI Administration (AI263)