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Get ready for a smarter Academy learning experience.

We’re enhancing the platform to deliver a smoother, more powerful AI learning journey.

To prepare for the migration, we recommend that you complete any courses in progress by April 8. A course is considered complete once all units have been finished and the final quiz has been passed. This ensures accurate history transfer.

System Migration (Offline):
Thursday April 9, Midnight PT — Monday April 13, 6:00 AM PT

Thank you for being part of our NVIDIA learning community. We can’t wait to show you what’s next.

Please review this FAQ for additional details.
Run:ai Platform Deployment
Interactive self-paced learning
$50 single course I $250 as part of Platinum membership
Course Duration 3 Hours
Why should I take this course?
What will I learn?
Course Topics
Course Objectives
Audience
Course Prerequisites
The Run:ai Platform Deployment course provides a practical, end-to-end introduction to deploying and configuring the Run:ai platform. This course covers both conceptual understanding and hands-on guidance for installing, configuring, and verifying Run:ai deployments.
Learn how to successfully deploy and configure the Run:ai platform, from understanding its architecture to completing installation and post-deployment setup. Gain practical knowledge on managing core resources, validating platform deployments, and running workloads. By the end of the course, you’ll be prepared to support real-world Run:ai deployment workflows in your environment.
• Overview of the Run:ai platform and architecture • Core building blocks: node pools and projects • Installation types and prerequisites • Installation demonstration • Post-installation configuration: CLI, SSO, and role-based access control (RBAC) • Deployment workflows and verification  • Running Workloads
• Understand the Run:ai platform architecture, core components, and building blocks (node pools, projects) • Identify installation types, prerequisites, and deployment requirements • Understand the workload types in Run:ai and how to run them • Describe a Run:ai installation and platform components configuration • Review post-installation settings, including CLI, SSO integration, and RBAC • Describe deployment workflows and verify successful platform setup.
The course is designed for Run:ai infrastructure administrators, DevOps professionals, and IT-related roles who want to gain the knowledge necessary to deploy and configure hte NVIDIA Run:ai platform.
• Basic understanding of Linux system administration and command-line operations • Familiarity with containerized environments (e.g., Docker or Kubernetes) • General knowledge of AI/ML workflows or GPU-accelerated workloads is beneficial • Experience with cluster or platform management is recommended
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