Program Outline
Deploying RAG Pipelines for Production at Scale
Teaches production-level deployment of LLM applications, especially enterprise-grade RAG pipelines.
Delivery
Virtual, On-site, or Hybrid
Duration
3 hours
Product
NVIDIA NIM
Role
AI Platform Engineer
NVIDIA
Generative AI / LLMDeploying RAG Pipelines for Production at Scale
NVIDIA NIM
Best Fit
Audience Profile
Who This Program Is For
Built for teams moving RAG systems into serious production environments.
Overview
Program Summary
Official NVIDIA self-paced course on production-scale deployment of RAG pipelines using NVIDIA NIM microservices.
Course Outline
Complete Module Sequence
Review the full module sequence for this program, including the primary topic coverage in each module where available.
1Module 1
Deploy RAG pipelines at scale
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Module 1
Deploy RAG pipelines at scale
Learn platform and deployment patterns for enterprise RAG systems.
- Production RAG architecture
- Deployment with NIM and Helm
Coverage Areas
Topic Coverage
Coverage Item 1
Production RAG architecture
Coverage Item 2
Deployment with NIM and Helm
Customization
Adapt This Program for Your Team
We can adapt this program around your team structure, platform priorities, delivery goals, and the scenarios your people need to work through in practice.
- •Use your target deployment environment
- •Add observability and scaling patterns
