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Exam Information
Official specifications published by NVIDIA
Exam Format
90 min
60-70
70%
Professional
Registration
$400 USD
Online Proctored or online proctoring
Validity
2 years
Retake the current version of the exam; Pass a higher-level NVIDIA certification exam
NCP-AIO Exam Topics and Domains
NCP-AIO is organized into 4 weighted domains. Expect to work with Kubernetes, DCGM, Docker, GPFS, and more.
1
Installation and Deployment
31%
Mission Control Toolkit
Mission Control Installation
- Install and configure Mission Control toolkit
- Validate deployment success
- Troubleshoot installation issues
Base Command Manager Administration
BCM Deployment and ConfigurationUser Account Management
- Deploy and configure Base Command Manager
- Manage user accounts and permissions
- Configure authentication and authorization
Job Scheduling Systems
Slurm Installation and ConfigurationKubernetes Deployment
- Install and configure Slurm for HPC workloads
- Deploy Kubernetes with GPU support
- Configure job scheduling policies
System Configuration
Network ConfigurationFirmware UpdatesDOCA Services Deployment
- Configure high-performance networking
- Manage firmware and driver updates
- Deploy DOCA services on DPUs
2
Administration
23%
Cluster Administration
Slurm Cluster AdministrationKubernetes Administration
- Administer Slurm clusters effectively
- Manage Kubernetes clusters for AI workloads
- Configure resource allocation policies
Data Center Architecture
GPU Cluster ArchitectureStorage Architecture
- Design efficient data center architectures
- Configure storage systems for AI workloads
- Optimize data locality and access patterns
GPU Virtualization
MIG ConfigurationvGPU Administration
- Configure Multi-Instance GPU (MIG)
- Implement GPU virtualization strategies
- Optimize GPU utilization
Run:ai Administration
Run:ai Platform Management
- Deploy and configure Run:ai platform
- Implement resource allocation policies
- Monitor workload distribution
3
Workload Management
23%
Training Workload Deployment
Deep Learning Training JobsHyperparameter Tuning
- Deploy deep learning training workloads
- Configure distributed training jobs
- Optimize resource utilization for training
Inference Workload Deployment
Model Serving InfrastructureReal-time Inference
- Deploy inference workloads efficiently
- Configure Triton Inference Server
- Optimize inference performance
Container Management
NGC Container DeploymentContainer Orchestration
- Deploy containers from NGC catalog
- Manage container lifecycles
- Configure container networking and storage
Resource Allocation
GPU Resource ManagementMemory and Storage Management
- Implement resource allocation strategies
- Optimize GPU utilization
- Manage memory and storage resources
4
Troubleshooting and Optimization
23%
Container Troubleshooting
Docker TroubleshootingContainer Deployment Issues
- Troubleshoot Docker container issues
- Resolve container deployment problems
- Analyze container logs effectively
GPU and Fabric Manager
Fabric Manager Service TroubleshootingGPU Health Monitoring
- Troubleshoot Fabric Manager issues
- Monitor and diagnose GPU health
- Optimize GPU interconnect performance
Base Command Manager Issues
BCM Service TroubleshootingCluster Management Issues
- Troubleshoot BCM service issues
- Resolve cluster management problems
- Maintain cluster health
Performance Optimization
Storage PerformanceNetwork PerformanceMagnum IO Components
- Optimize storage performance
- Tune network for AI workloads
- Configure Magnum IO components
How do I earn this certification?
Passing NCP-AIO earns the NVIDIA Certified Professional - AI Operations certification. It sits in the AI Infrastructure and Operations track.
Current Level Exams
- NCP-AII - AI Infrastructure Professional
- NCP-AIN - AI Networking Professional
- NCP-ADS - Accelerated Data Science Professional
Next Level Options
Expert Level - NVIDIA Expert Certifications (Coming Soon) Expert level certifications are in development
Alternative Paths
- NCA-GenAI-LLM - Generative AI with LLMs Associate Complementary AI application development skills
- NCA-GenAI-MM - Generative AI Multimodal Associate Multimodal AI system design skills
- DLI-Courses - Deep Learning Institute Specializations Hands-on training for specific technologies
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
Use the official PlanetCert Practice Test alongside the study plan below to prepare efficiently for NCP-AIO.
What's changed on this exam?
Current Status
- ACTIVE
- Last content update: 2024-06-15
- Announcement date: 2023-06-01
Updates
- Multi-Instance GPU (MIG) Blackwell Generation Universal MIG now supports graphics workloads, up to 4 instances on RTX PRO 6000 • Release date: 2024-09-01
- Base Command Manager 11.0 New Power Reservation Steering and performance profiles are exam topics • Release date: 2024-08-01
- NVIDIA AI Enterprise 5.0 Integration with Mission Control platform for AI factory operations • Release date: 2024-07-01
- Run:ai 2.15 Enhanced integration with BCM via cm-kubernetes-setup wizard • Release date: 2024-06-15
- NVIDIA Fabric Manager 560 Support for Blackwell NVSwitch and NVLink 5.0 • Release date: 2024-08-01
Who should take this exam?
This exam is typically taken by MLOps Engineers and DevOps Engineers.
- 2-3 years of operational experience working in a data center with NVIDIA hardware solutions
- Experience with Linux system administration
- Knowledge of container technologies (Docker, Kubernetes)
- Understanding of HPC job scheduling (Slurm)
- Basic understanding of AI/ML workloads