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Join our Red Hat® experts for an insightful Tech Journey series designed to help put artificial intelligence (AI) to work for you, the open source way. Take a look at the sessions taking place over the coming months and register for those that interest you.
What you’ll experience:
Product insights: Learn how Red Hat AI platforms help accelerate AI adoption, abstract the complexities of delivering AI solutions, and bring flexibility to develop and deploy wherever your data resides.
Live demonstrations: See the platforms’ capabilities in action with real-world use cases.
Hands-on workshops: Build, test, and deploy tailored enterprise AI solutions in interactive sessions guided by experts.
Who should attend?
IT professionals, Data scientists, Developers and AI engineers.
NEXT SESSIONS
The key challenges of adopting AI are cost, complexity, and flexibility. Model training is often costly and unsuitable for all use cases, too complex for non-data scientists, and limited to specific cloud environments.
Red Hat Enterprise Linux® AI is affordable and can run on a single server, which is great for those starting out with gen AI. It provides a foundation model platform that runs on Dell PowerEdge where customers are in production. Using InstructLAB, a new way of fine tuning models, it provides an accessible recipe for finetuning small models based on the popular and easy to use YAML scripting language. Join the demo to find out more.
SPEAKERS:
Camille Nigon Junior Solutions Architect Red Hat
Dirk Zielinski Cloud Solution Architect EMEA Dell
As AI adoption accelerates, managing multiple models across departments and users remains a challenge. Model-as-a-Service (MaaS) helps address this by enabling organizations to deploy pre-trained AI models as scalable services, accessible via API gateways on hybrid cloud platforms.
Join this session to learn how to implement a MaaS platform using Red Hat OpenShift® and Red at OpenShift AI. Our experts will show you how to:
Ensure the right users and teams have secure access to the models they need.
Enable multitenancy, allowing teams to work independently in secure, isolated environments on a shared platform.
Easily scale the platform to meet growing model usage and user demand.
SPEAKER:
Codrin Bucur AI Platform SSA, EMEA Red Hat
In January 2025, Red Hat acquired Neural Magic—a pioneer in software and algorithms that accelerate gen AI inference workloads —to tackle the challenges of enterprise AI and further democratize access to its transformative power through open source innovation.
Join this expert-led webinar to discover how you can streamline AI model deployment with Neural Magic.
SPEAKER:
Codrin Bucur AI Platform SSA, EMEA Red Hat
On-demand Sessions
How can you easily get started with gen AI, whether you have a Kubernetes platform in place or not? Discover the best starting points based on where you are in your application platform journey.
SPEAKER:
Andreas Bergqvist Red Hat AI Sales Specialist, EMEA Red Hat
Join us for this demo, where we’ll explore how to improve a Large Language Model (LLM) in an accessible way using InstructLab. We’ll cover:
The role of InstructLab in training and enhancing LLMs
A guided walkthrough of InstructLab’s tools to download, serve and interact with a pre-trained LLM
A demonstration of how to apply InstructLab to a real-world insurance application
Techniques for generating synthetic data and integrating structured knowledge with InstructLab to enhance an LLM's capabilities
This demo is ideal for professionals and enthusiasts eager to discover how LLMs can be tailored for specialized tasks with minimal technical barriers.
SPEAKER:
Pauline Truong AI Specialist Solution Architect Red Hat
Learn how to leverage Red Hat OpenShift AI, running on top of Azure Red Hat OpenShift, with the Microsoft AI ecosystem to accelerate your journey to production AI applications.
You’ll experience what it is like to go from an idea to evaluating foundation models to tuning a model, add data retrieval enhancements with RAG, and then deliver a production-ready application that delivers the business value of gen AI.
SPEAKERS:
Rhys Powell Senior Black Belt, Managed OpenShift Red Hat
Andy Repton Senior Black Belt, Managed OpenShift Red Hat
Do you want to ensure your platform supports the latest AI models while meeting the quality, reliability, and standards required for your enterprise IT environment?
Join this demo to learn how you can benefit from Red Hat and Dell’s “Model as a Service”, a pattern for making predictive and generative models servable where you remain in control.
SPEAKERS:
Kristoffer Nærland-Sohrt EMEA Ecosystem Specialist Sales - AppDev & AI/ML Red Hat
Paul Wynne Global Lead AI Field Strategy | CSC Dell Technologies
Laura Dragan Cloud Engineer | Multicloud Specialty Team Dell Technologies
Join us for this Red Hat Skill Builders episode and learn how Red Hat Learning Subscription Premium can boost your AI journey. Offering instructor-led, live virtual sessions alongside its self-paced online courses and hands-on labs, RHLS will prepare your organization to get maximum value from your Red Hat AI investment.
During this webinar you will learn how to:
Part 1: Identify AI knowledge domains and personal gap areas.
Part 2: Set-up AI learning goals and aggregate RHLS learning resources, around your own AI journey.
Part 3: Explore AI/ML products and use cases, after having defined AI/ML prerequisites.
Part 4: Assess achievements, evaluate results, refine usage.
SPEAKER:
Erminio Cassella Specialist Solution Architect, Training and Certification Red Hat
Red Hat OpenShift AI offers an integrated user interface (UI) experience with tooling for building, training, tuning, deploying, and monitoring predictive and gen AI models.
Join us for an interactive, hands-on session showcasing OpenShift AI’s versatility in serving both gen AI and predictive AI simultaneously. You’ll also discover ways to enhance your AI skills.
SPEAKER:
Codrin Bucur AI Platform SSA, EMEA Red Hat
Join this demo to learn how to integrate AI models served by OpenShift AI within Java applications, using technologies like Quarkus, LangChain4J, and vLLM to efficiently deploy and serve large language models.