OVERVIEW
Build, train, and deploy AI-enabled applications into production faster with a hybrid MLOps platform
About event:
A single-day experience, the OpenShift AI roadshow gives attendees insight into how organizations 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.
What you’ll learn and experience:
- AI/ML market, technology, and operational trends that will help inform your organization’s AI/ML initiatives.
- How a hybrid MLOps platform - and its partner ecosystem - eases collaboration between IT, data science, and application development teams to enable faster innovation.
- Use case and implementation lessons other organizations have learned from starting or optimizing their AI/ML software application delivery process.
- Hands-on experience working with a MLOps platform. Key lessons include working with data science projects and workbenches, training different models and measuring accuracy, serving and deploying models, integrating different models and capabilities into a frontend application, and testing the application as a user. No AI experience is required.
Who should attend:
- Data engineers
- Data scientists
- ML engineer
- IT decision makers
- IT directors
- Infrastructure architects
- Infrastructure specialists
- Enterprise architects
- Developers
- Application architects
- Enterprise architects
- Developer team leads
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 web browser.
- Entry-level Kubernetes concepts
- A general understanding of Linux containers (e.g., Docker, CRI-O, etc.).
- No AI experience is required.
Agenda:
|
Time
|
Session
|
| 12:00 - 1:00 |
Registration, Welcome & Lunch |
| 1:00 - 1:30 |
How the AI/ML landscape is evolving |
| 1:30 - 2:00 |
How Red Hat customers are finding success with AI-enabled software applications |
| 2:00 - 2:30 |
Red Hat’s AI/ML partner ecosystem and Q&A |
| 2:30 - 5:00 |
Hands-on Lab: Use AI/ML to help insurance adjusters be more productive |
| 5:00 - 6:00 |
Networking Reception |
