“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
NVIDIAAdvanced
Deploying RAG Pipelines for Production at Scale
Teaches production-level deployment of LLM applications, especially enterprise-grade RAG pipelines.
Duration
3 hours
Level
Advanced
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
Enterprise Track
NVIDIA
Generative AI / LLMAI
Deploying RAG Pipelines for Production at Scale
NVIDIA NIM
NVIDIA
On this page
Ideal for
AI Platform EngineerGenerative AI / LLMTailored Team DeliveryImplementation-Focused
Audience Profile
Built for these roles
Built for teams moving RAG systems into serious production environments.
Overview
Executive overview
Official NVIDIA self-paced course on production-scale deployment of RAG pipelines using NVIDIA NIM microservices.
Readiness
Prerequisites
- Familiarity with LLM applications, RAG pipelines, Kubernetes, and Helm.
Program Outcomes
Capabilities your teams will gain
Understand production RAG deployment patterns
Use deployment concepts for enterprise-grade LLM applications
Curriculum
Curriculum roadmap
1
Production RAG architecture
2
Deployment with NIM and Helm
1Module 1
Deploy RAG pipelines at scale
+
Module 1
Deploy RAG pipelines at scale
Learn platform and deployment patterns for enterprise RAG systems.
- Production RAG architecture
- Deployment with NIM and Helm
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Implementation-focused labsPrivate cohort deliveryAdvanced practitioner depthBusiness outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Moves RAG work from prototype to production with deployment-focused guidance.
- •Use your target deployment environment
- •Add observability and scaling patterns
Credentials
Certification & official source
Aligned to the official source referenced for this program.
View Official SourceResources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
Retail & E-commerce
Representative Retail Analytics Team
Instead of treating reporting as a tooling issue alone, the work focused on consistency, governance, and shared delivery practices across analysts and engineering teams.
- Higher consistency in report design practices
- Improved collaboration between analysts and engineering teams
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
