NVIDIA certifications
Thirteen NVIDIA certifications across generative AI, AI infrastructure, data science and OpenUSD, prepared exam by exam with practice tests weighted like each exam guide and an AI tutor that explains every answer in your style.
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Certification paths
NVIDIA certifications come in two levels. One-hour Associate exams check the concepts; two-hour Professional exams check that you can do the job, from fine-tuning LLMs and building agents to bringing up and running AI data centers. Select any certification to see its exam.
Generative AI
Build LLM apps, agents and models
AI infrastructure
Build and run AI data centers
Data science
GPU-accelerated data and ML
Simulation
3D pipelines with OpenUSD
All NVIDIA certifications
Filter by track or level. Every card shows the exam you’ll sit, straight from its page on nvidia.com: how many questions, how long it runs and what it costs.
13 certifications
AssociateGenerative AI
Associate AI Developer
The foundations of building and maintaining LLM applications with NVIDIA tools: machine learning, data analysis, experimentation, software development and trustworthy AI.
Recommended: A basic understanding of generative AI and LLMs
AssociateGenerative AI
Associate AI Developer
Design, build and manage AI systems that work across text, images and audio.
Recommended: A basic understanding of generative AI
AssociateGenerative AI
Entry-level AI Developer
Customize, serve and evaluate AI models on NVIDIA’s platform: data processing, fine-tuning, inference, retrieval pipelines and agentic systems.
Recommended: None set; built for entry-level AI developers
ProfessionalGenerative AI
LLM Engineer
Design, train and optimize LLMs: distributed training, parameter-efficient fine-tuning and high-performance inference.
Recommended: 2–3 years in AI or ML roles working with LLMs
ProfessionalGenerative AI
AI Agent Engineer
Build and govern agentic AI systems: multi-agent architectures, orchestration, tool use, scale and safeguards.
Recommended: 1–2 years in AI or ML, with production agentic AI projects
AssociateAI infrastructure
IT professional new to AI infrastructure
The building blocks of AI computing in the data center: essential AI knowledge, AI infrastructure and AI operations.
Recommended: A basic understanding of data center infrastructure
ProfessionalAI infrastructure
AI Infrastructure Engineer
Deploy, configure and validate GPU servers and AI clusters: system bring-up, control plane setup, cluster testing and troubleshooting.
Recommended: 2–3 years deploying GPU servers and AI clusters
ProfessionalAI infrastructure
AI Operations Engineer
Monitor, administer and troubleshoot NVIDIA AI infrastructure: installation, administration, workload management and optimization.
Recommended: 2–3 years running data centers with NVIDIA hardware
ProfessionalAI infrastructure
AI Network Engineer
Deploy and run networks for AI: Spectrum-X Ethernet, InfiniBand, Kubernetes integration, automation and troubleshooting, with a hands-on lab in the exam.
Recommended: 2–3 years of data center networking
ProfessionalAI infrastructure
Data Center Infrastructure Technician
Install, cable and connect NVIDIA AI systems safely: site planning, rack preparation, high-density cabling, testing and documentation.
Recommended: 2+ years in data center operations with high-density computing
AssociateData science
Data Scientist
GPU-accelerated data science: preparing data, developing models and managing end-to-end workflows.
Recommended: 1–2 years in accelerated data science
ProfessionalData science
Senior Data Scientist
GPU-accelerated tools and libraries across the data science workflow, and the optimization strategies that make them fast.
Recommended: 2–3 years in accelerated data science
ProfessionalSimulation
3D Pipeline Developer
Build, maintain and optimize 3D content pipelines with OpenUSD.
Recommended: 2–3 years with OpenUSD and Python or C++
Exam details from each certification’s page on nvidia.com, checked weekly for changes; last updated November 7, 2026. Exams are pass/fail and NVIDIA doesn’t publish passing scores. Every NVIDIA certification is valid for two years. NVIDIA and the names of its certifications are trademarks of NVIDIA Corporation.
Built for NVIDIA exams
NVIDIA exams follow the topic weights in each exam guide, and Professional exams expect hands-on skill. Every tool works toward the exam you’ll actually sit.
Practice exams weighted like each NVIDIA exam guide’s topics and timed like the real thing: one hour for Associate, two for Professional.
Learn more: Timed practice examsProfessional exams test what you can do. Practice the deployment, training and troubleshooting tasks they cover in guided labs.
Learn more: Hands-on labsWork through situations from AI teams and data centers, and see what each decision leads to.
Learn more: Real-world scenariosGot one wrong? The tutor explains why, in the way you learn best, and points to the exam topic behind it.
Learn more: An AI tutor on every answerA readiness score across every topic in the exam guide, so you book the exam when the numbers say you’ll pass.
Learn more: Know when you’re readyFAQs
Find quick answers or contact our support team.
Start with the Associate exam for your area: Generative AI LLMs or AI Models and Application Development for developers, AI Infrastructure and Operations for IT and data center roles, Accelerated Data Science for data scientists. Professional exams expect two to three years of hands-on experience.
Associate exams run one hour with 50 to 60 questions. Professional exams run two hours, most with 60 to 75 questions; AI Operations has 30, and AI Networking includes a hands-on lab.
$125 for an Associate exam. Professional exams cost $200, except AI Infrastructure and AI Rack and Interconnect ($400) and AI Operations and AI Networking ($500). Taxes may apply in some countries.
NVIDIA doesn’t publish it. Exams are scored pass/fail.
Two years from the day it’s issued. To recertify, you take the current exam again.
Yes. NVIDIA exams are proctored remotely through Certiverse, and breaks aren’t allowed. You can schedule up to 60 days ahead and cancel or reschedule up to 24 hours before.
Yes. The free plan includes 200 credits you can spend across the platform, with no credit card required. Upgrade to Pro whenever you want unlimited practice.
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