“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
Track: NVIDIA DLI Certificate of Competency
NVIDIAIntermediate
Building RAG Agents with LLMs
This NVIDIA DLI course teaches teams how to design retrieval-augmented generation systems and bundle them into deliverable formats. It also explores advanced LLM composition techniques for internal reasoning, dialog management, and tooling.
Duration
8 hours
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
Executive brief for stakeholdersDownload Program Brief (PDF)
In Demand
NVIDIA
Agentic LLM SystemsAG
Grounding, tools, orchestration
NVIDIA RAG Agents
RAG
On this page
Ideal for
AI / LLM EngineerRAG AgentsTailored Team DeliveryImplementation-Focused
How VNode delivers this
Who this is for, and how we run it
VNode ITeS delivers Building RAG Agents with LLMs as an MCT-led NVIDIA program for AI / LLM Engineer. Typical duration is 8 hours (Virtual, On-site, or Hybrid). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
Built for practitioners who want to move from general LLM usage into retrieval-grounded and agentic system design for production-facing solutions.
Overview
Executive overview
Official NVIDIA DLI generative AI program focused on retrieval-augmented generation systems and agent-based LLM workflows.
Readiness
Prerequisites
- Relevant foundational experience in the target technology area.
- Comfort with hands-on labs in a cloud or GPU-accelerated environment.
Program Outcomes
Capabilities your teams will gain
Strengthen capability in rag agents scenarios
Strengthen capability in nvidia nemo scenarios
Strengthen capability in generative ai / llm scenarios
Curriculum
Curriculum roadmap
1
RAG Agents
2
NVIDIA NeMo
3
Generative AI / LLM
1Module 1
RAG Agents
+
Module 1
RAG Agents
Cover rag agents skills and implementation practices aligned to Building RAG Agents with LLMs.
- Cover rag agents skills
- implementation practices aligned to Building RAG Agents with LLMs
2Module 2
NVIDIA NeMo
+
Module 2
NVIDIA NeMo
Cover nvidia nemo skills and implementation practices aligned to Building RAG Agents with LLMs.
- Cover nvidia nemo skills
- implementation practices aligned to Building RAG Agents with LLMs
3Module 3
Generative AI / LLM
+
Module 3
Generative AI / LLM
Cover generative ai / llm skills and implementation practices aligned to Building RAG Agents with LLMs.
- Cover generative ai / llm skills
- implementation practices aligned to Building RAG Agents with LLMs
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
Implementation-focused labsPrivate cohort deliveryIntermediate practitioner depthBusiness outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Directly supports enterprise GenAI adoption by helping teams build retrieval-based, tool-using LLM agents that can support real business workflows.
- •Use your enterprise knowledge or document workflow as the basis
- •Add governance and evaluation emphasis for regulated scenarios
- •Extend into deployment, serving, and operationalization decisions
Credentials
Certification & official source
- •NVIDIA DLI Certificate of Competency
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