A single day experience, the OpenShift AI roadshow gives attendees insight into how organisations are using, delivering, monitoring AI-enabled applications with speed across the hybrid cloud. As part of the roadshow – IT operations, data engineers, data scientists, and application developers will have the opportunity to build, train, and deploy an AI model and integrate it into an application with a hands-on lab. They’ll experience what it is like to go from an idea to building an accurate model to having a production-ready application.

In this session you will:

• Hear how Red Hat's hybrid AI platforms are unlocking opportunities for organisations to benefit from predictive and generative AI
• Experience how InstructLab simplifies GenAI model alignment tuning and promotes community-based development; opening the ability for any line-of-business domain expert to directly contribute knowledge and skills to models
• Practice working with a hybrid-cloud MLOps platform, including: working with data science projects and workbenches, training models and measuring accuracy, serving and deploying models, integrating different models and capabilities into a frontend application, and testing the application as a user

Who should attend:

• Data Engineers, Data Scientists, ML engineers
• Developers and Developer team leads
• Application architects, Enterprise architects
• Infrastructure architects, Infrastructure specialists
• IT decision makers, IT directors

Important: Please bring a laptop to access this hands-on experience. Kindly ensure that your laptop should have a modern web browser that can operate without a VPN connection. Wifi network will be provided. While our preferred browser is Google Chrome, Firefox, Safari, and Edge should also be compatible.

Know before you go

Operations, developers, and data science practitioners doing the hands-on lab should have these suggested tools and knowledge of these areas:

• A laptop computer running Windows, MacOS, or Linux with the Firefox or Chrome-based web browser (a Chrome-based browser is preferred)
• An entry-level understanding of Linux and containers (e.g., Docker, Kubernetes, etc.)
• A basic understanding of generative AI and machine learning concepts(e.g., machine learning, deep learning, foundation models, etc.) will be beneficial