Course Contents

Use the navigation tabs above to explore each topic in the lab.

Lab Sections

1. Projects - Your workspace allocation and GPU quota
2. Credentials - Docker registry and S3 credentials for your workloads
3. Data Sources - Connecting datasets to your training jobs
4. Environments - Pre-built container images for ML frameworks
5. Workspaces - Interactive Jupyter notebooks with GPU access
6. Training - Submitting distributed training jobs
7. Inference - Deploying models as API endpoints

Quick Links

• Run:AI Documentation: https://docs.run.ai
• NVIDIA NGC Catalog: https://catalog.ngc.nvidia.com

If you run into issues, raise your hand and an instructor will assist you.