This three-day course 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.
Comprehend the fundamentals of generative AI
Understand the capabilities of the Granite models to solve enterprise use cases
Train, deploy, and serve large language models with Red Hat Enterprise Linux AI
Red Hat is the leading provider of open source, enterprise IT solutions. Lumify Work is proud to offer clients the ability to attend over 40 official Red Hat training courses through a resell agreement with Red Hat. Maximise the return on your Red Hat technology investment with lab-intensive, instructor-led training run by Red Hat themselves.
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.
A basic understanding of AI & ML is recommended but not required
Familiarity with the Linux command line
Lumify Work offers certification and training in Enterprise Linux, Ansible, JBoss, OpenShift, OpenStack, and more through our partnership with Red Hat. This arrangement requires Lumify Work to provide your details to Red Hat for course and/or exam registration purposes.
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
