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Develop, Test, and Run Granite Family LLMs with Red Hat Enterprise Linux AI Virtual Training (AI296LS)
- Categories:
- Artificial Intelligence Infrastructure and Networking
- Level:
- Intermediate
- Code:
- AI296LS
- Exam:
- Yes - Included
Overview
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 1.5.
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.
What's included
This product includes the following:
- A seat on any public schedule virtual training date within 12 months of purchase of the RHLS Course Product
- 24/7 access to RHLS Digital content and labs equivalent to the classroom syllabus of the Virtual training course which you can consume as often as you wish within 12 months of purchase, before or after attending your virtual classroom event
- An exam voucher which you can redeem to book on any Red Hat exam
- Exam preparation aids
- Chat based access to a subject matter expert to help you prepare for your exam or generally assist you with queries relating to the course syllabus
Prerequisites
- A basic understanding of AI & ML is recommended but not required.
- Familiarity with the Linux command line.
- Technology considerations
- For virtual, self-paced, and classroom learners:
- Internet access is required
- Labs are performed in Red Hat's Online Learning Environment
- For classroom learners, Red Hat may make available in the future a locally installed classroom environment as an alternative.
What's included
Select your preferred way to learn:
What is Classroom?
Hands-on, instructor-led training delivered in a QA learning centre
In-person training in a dedicated QA learning centre. Learners benefit from expert-led sessions, collaborative activities, and structured, hands-on workshops in a distraction-free environment. If you can’t attend in person, many classroom courses are also available to attend remotely.
Classroom sessions can be arranged on request. Please contact your account manager to discuss availability in your region
Best for: Individuals and teams who benefit from deep focus, direct interaction, and practical, hands-on learning.
What's included?
2 Days instructor led course
Exam included
6 month free access to QA learning platform
Free 6-Month Access: Learning Platform Discovery plan
Included FREE with every instructor‑led course
Get free guided access to the QA Learning Platform. Assess your skills, explore in-demand topics, and understand which areas to focus on.
Learn AI, Cloud, Data, and Leadership skills at your own pace.
Put skills into practice with hands-on Labs and Simulabs.
Validate knowledge and highlight gaps with skills assessments.
What is bespoke training?
Custom instructor-led training designed by QA to fit your needs
Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.
Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.
Find out more about the course:
Learning outcomes
- 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
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.
Good to know
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What our customers are saying
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Global Partner Sales Executive, Microsoft Worldwide Learning
"The AI Champions Pathway was invaluable at really helping to super-charge AI adoption across Awaze... we've seen the application of AI-first thinking grow rapidly; from simple everyday ChatGPT usage for communications, to the creation of GPTs, to evolved complaints handling processes. As a business, we now see innovative, AI-first thinking as a key enabler to our strategic priorities, rather than a nice-to-have.”
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People Transformation Lead, Awaze
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Tatiana Arventi
Senior Go To Market Manager - M365 Copilot Microsoft UK
Portfolio Director
Dr Vicky Crockett
Portfolio Director – Artificial Intelligence
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