“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Enterprise Program Brief
Getting Started with Accelerated Computing in Modern CUDA C++
Official NVIDIA Deep Learning Institute program covering cuda c++ with hands-on GPU-accelerated labs.
Duration
8 hours
Level
Beginner
Format
Virtual, On-site, or Hybrid
Language
English
NVIDIA
CUDA C++Getting Started with Accelerated Computing in Modern CUDA C++
CUDA
On this page
Ideal for
Audience Profile
Built for these roles
Built for Deep Learning Practitioner learners adopting Getting Started with Accelerated Computing in Modern CUDA C++.
Overview
Executive overview
NVIDIA Deep Learning Institute-aligned program for Getting Started with Accelerated Computing in Modern CUDA C++.
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 cuda c++ scenarios
Strengthen capability in cuda scenarios
Strengthen capability in deep learning scenarios
Curriculum
Curriculum roadmap
CUDA C++
CUDA
Deep Learning
1Module 1
CUDA C++
+
Module 1
CUDA C++
Cover cuda c++ skills and implementation practices aligned to Getting Started with Accelerated Computing in Modern CUDA C++.
- Cover cuda c++ skills
- implementation practices aligned to Getting Started with Accelerated Computing in Modern CUDA C++
2Module 2
CUDA
+
Module 2
CUDA
Cover cuda skills and implementation practices aligned to Getting Started with Accelerated Computing in Modern CUDA C++.
- Cover cuda skills
- implementation practices aligned to Getting Started with Accelerated Computing in Modern CUDA C++
3Module 3
Deep Learning
+
Module 3
Deep Learning
Cover deep learning skills and implementation practices aligned to Getting Started with Accelerated Computing in Modern CUDA C++.
- Cover deep learning skills
- implementation practices aligned to Getting Started with Accelerated Computing in Modern CUDA C++
Delivery Models
Delivery models
Engagement Fit
Engagement fit
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Builds NVIDIA GPU-accelerated skills for cuda c++ with hands-on DLI-style labs.
- •Align labs to your production environment and platform priorities
- •Add readiness reviews and instructor-led practice sessions
- •Extend into project-specific architecture or delivery coaching
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
