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Exam Information
Official specifications published by NVIDIA
Exam Format
60 min
50
70%
Associate
Registration
$125 USD
Online Proctored or online proctoring
English
Validity
2 years
Retake the current version of the exam; Pass a higher-level NVIDIA certification
NCA-AIIO Exam Topics and Domains
NCA-AIIO is organized into 3 weighted domains. Expect to work with NVIDIA AI Enterprise, NVIDIA Data Center GPU Manager (DCGM), NVIDIA DGX Systems, NVIDIA RAPIDS, and more.
1
Essential AI Knowledge
33%
AI Fundamentals
AI, Machine Learning, and Deep Learning ConceptsAI Use Cases and Industry Applications
- Explain AI terminology and fundamental concepts
- Identify major AI use cases across various industries
- Understand the factors driving AI adoption
- Differentiate between AI, machine learning, and deep learning
GPU Computing Architecture
GPU vs CPU ArchitectureNVIDIA GPU Generations
- Describe how GPU computing contributes to AI advancement
- Compare and contrast GPU and CPU architectures
- Understand NVIDIA GPU technology evolution
NVIDIA Software Stack
AI Development Software ComponentsFrameworks and Libraries
- Understand the NVIDIA software stack components
- Describe the purpose of various NVIDIA software solutions
- Identify software components in the AI development lifecycle
2
AI Infrastructure
34%
Compute Platforms
NVIDIA DGX SystemsNVIDIA HGX Platform
- Identify NVIDIA compute platform options
- Understand DGX and HGX system capabilities
- Select appropriate hardware for AI workloads
Networking for AI
High-Performance NetworkingGPU Direct Technologies
- Understand networking requirements for AI infrastructure
- Identify appropriate networking technologies
- Optimize network architecture for AI workloads
Storage for AI
Storage Architecture and RequirementsData Pipeline Optimization
- Understand storage requirements for AI workloads
- Design efficient data pipelines
- Optimize storage architecture for performance
Energy Efficiency and Cooling
Power ManagementCooling Solutions
- Understand energy requirements for AI data centers
- Implement energy-efficient computing practices
- Design appropriate cooling solutions
Cloud and Hybrid Deployments
On-Premises vs Cloud InfrastructureReference Architectures
- Compare on-premises and cloud AI solutions
- Understand reference architectures
- Design hybrid AI infrastructure
3
AI Operations
33%
Infrastructure Management
Cluster Management ToolsVirtualization and Multi-Tenancy
- Describe essentials for AI data center management
- Understand cluster orchestration principles
- Implement virtualization strategies
Monitoring and Observability
GPU MonitoringPerformance Analysis
- Monitor GPU infrastructure effectively
- Analyze performance metrics
- Implement observability best practices
Job Scheduling and Workload Management
Job Scheduling SystemsResource Management
- Understand job scheduling for AI workloads
- Implement resource management strategies
- Optimize workload distribution
MLOps and AI Lifecycle Management
MLOps FundamentalsProduction Deployment
- Understand MLOps principles and practices
- Implement AI lifecycle management
- Deploy and monitor models in production
How do I earn this certification?
Passing NCA-AIIO earns the NVIDIA Certified Associate - AI Infrastructure and Operations certification. It sits in the AI Infrastructure and Operations track.
Current Level Exams
- NCA-GenL - Generative AI with LLMs
- NCA-MMA - Multimodal Generative AI
Next Level Options
- NCP-AII - NVIDIA Certified Professional - AI Infrastructure
- NCP-AIO - NVIDIA Certified Professional - AI Operations
Alternative Paths
- NCA-GenL - Generative AI with LLMsExpand into generative AI applications
- DLI-Courses - Deep Learning Institute Specializations Hands-on deep learning skills development
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
The most effective way to prepare for NCA-AIIO is by using the PlanetCert Simulator to practice questions and review detailed explanations.
What's changed on this exam?
Current Status
- ACTIVE
- Last content update: 2024-01-01
- Announcement date: 2024-01-01
Updates
- NVIDIA H200 Tensor Core GPU GA Core topic for current infrastructure questions • Release date: 2024-Q2
- NVIDIA AI Enterprise 5.0 Updated software stack questions • Release date: 2024-Q3
- NVIDIA GPU Operator 23.9.0 Kubernetes GPU management topics • Release date: 2024-Q1
- Multi-Instance GPU (MIG) 3.0 Resource partitioning and multi-tenancy questions • Release date: 2023-Q4
Who should take this exam?
This exam is typically taken by IT Professionals and System Administrators.
- Basic understanding of data center infrastructure
- Familiarity with Linux operating systems
- General IT knowledge
- Understanding of networking concepts