“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
Generative AI With Diffusion Models
This NVIDIA DLI course helps teams get started with generative AI application development by building a text-to-image solution with diffusion models. It combines from-scratch understanding with enterprise use of pretrained approaches to accelerate application delivery.
Duration
8 hours
Level
Intermediate
Format
Virtual, On-site, or Hybrid
Language
English
NVIDIA
Generative ImagingText-to-image and diffusion workflows
NVIDIA Diffusion
On this page
Ideal for
Audience Profile
Built for these roles
Built for practitioners with solid deep learning foundations who want to expand into enterprise image-generative AI workflows using diffusion models.
Overview
Executive overview
Official NVIDIA DLI generative AI course focused on building text-to-image applications with diffusion models.
Readiness
Prerequisites
- Good understanding of PyTorch.
- Good understanding of deep learning.
Program Outcomes
Capabilities your teams will gain
Build text-to-image applications with diffusion models
Understand denoising diffusion model components and control patterns
Use pretrained approaches to accelerate solution development
Strengthen enterprise generative AI engineering capability beyond LLM-only workflows
Curriculum
Curriculum roadmap
Diffusion model foundations
Text-to-image generation workflows
Pretrained model acceleration
Optimization and output control
1Module 1
Understand diffusion-based generation
+
Module 1
Understand diffusion-based generation
Learn the core ideas behind diffusion models and how they support modern image-generative AI applications.
- Diffusion model foundations
- Text-to-image generation workflows
2Module 2
Accelerate and refine image generation solutions
+
Module 2
Accelerate and refine image generation solutions
Use pretrained approaches and optimization techniques to improve output quality, speed development, and support more controlled generation.
- Pretrained model acceleration
- Optimization and output control
Delivery Models
Delivery models
Engagement Fit
Engagement fit
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Expands team capability beyond text-based GenAI by building working understanding of image generation workflows and diffusion-model implementation patterns.
- •Use your visual content use case as the workshop context
- •Add multimodal and evaluation follow-on topics
- •Extend into deployment and product-integration considerations
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
