AI296
Develop, Test, and Run Granite Family LLMs with Red Hat Enterprise Linux AI
Overview
Course Description
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.
This course is based on Red Hat Enterprise Linux AI 1.4.
Note: This course is offered as a 2 day in person class, a 3 day virtual class, or is self-paced. Durations may vary depending on the delivery method. For full course details, scheduling, and pricing, select your location and then click “Get Started” on the right-hand menu.
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
Target Audience
- 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.
Recommended training
- A basic understanding of AI & ML is recommended but not required.
- Familiarity with the Linux command line.
Technology considerations
- Technically it is possible to do this course as BYOD if the student has access to a RHEL AI machine that meets the minimum requirements.
- The course is not using GPUs, for the exercises that require GPUs, we provide a video and instructions for those students with access to a RHEL AI machine.
Outline
Course Outline
Generative AI Fundamentals: Capabilities, Challenges, Models, and Techniques
Define Generative AI, its importance, benefits, and challenges. Learn to select suitable GenAI and LLM models and techniques, considering their capabilities, use cases, and limitations.
Granite Models For Enterprise Generative AI
Describe and understand Granite models, and their capabilities to solve enterprise use cases, compared to larger, closed models.
Training Large Language Models with Red Hat Enterprise Linux AI
Enable technical and non-technical stakeholders to collaborate in the creation, training, and deployment of large language models (LLMs) optimized for specific business needs by using Red Hat Enterprise Linux AI and IBM Granite.
Deploying Trained Models with Red Hat Enterprise Linux AI
Deploy, serve, and operate generative AI models trained with Red Hat Enterprise Linux AI.
Outcomes
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.
