Who should attend
- Data Scientists and AI specialists who want to learn more about Granite models and the process of training and aligning GenAI models for specific business requirements.
- Developers with basic AI/ML knowledge or machine learning engineers who are interested in learning how to develop, test, and run AI-based enterprise applications in an enterprise and secure environment.
- System administrators who are interested in learning how to manage the company’s hybrid cloud infrastructure to boost the adoption of generative AI and LLMs, while enforcing security policies.
- Other professionals, such as SMEs and domain experts, who are interested in learning how to contribute to the training of secure models tailored to their business needs.
Prerequisites
- A basic understanding of AI & ML is recommended but not required.
- Familiarity with the Linux command line.
Course Objectives
Impact on the Organization
Organizations collect and store vast amounts of information from multiple sources. With Red Hat Enterprise Linux AI, organizations can enhance their ability to securely train and deploy large language models (LLMs) tailored to their specific business requirements.
Impact on the Individual
As a result of attending this course, you will comprehend the fundamentals of generative AI. You will be able to understand the capabilities of the Granite models to solve enterprise use cases. Finally, you will be able to train, deploy, and serve large language models with Red Hat Enterprise Linux AI.
Course Content
An introduction to fine-tuning, serving, and using generative AI models with Red Hat Enterprise Linux AI.
Develop, Test, and Run Granite Family LLMs with Red Hat Enterprise Linux AI (AI296) provides students with the fundamental knowledge about how to fine-tune, serve, and use generative AI models tailored to specific business needs. This course helps students build core skills to train models in a secure and private environment.
Course Content Summary
- Generative AI Fundamentals: Capabilities, Challenges, Models, and Techniques
- Granite Models For Enterprise Generative AI
- Training Large Language Models with Red Hat Enterprise Linux AI
- Deploying Trained Models with Red Hat Enterprise Linux AI