NVIDIA-Certified Professional

AI Operations

(NCP-AIO)

About This Certification
Exam Preparation
Exam Study Guide
Contact Us
Stay Informed

About This Certification
Exam Preparation
Exam Study Guide
Contact Us
Stay Informed

About This Certification

The NCP-AI Operations certification is an intermediate-level credential that validates a candidate’s ability to monitor, troubleshoot, and optimize AI infrastructure by NVIDIA. The exam is online and proctored remotely, includes 50 questions, and has a 90-minute time limit.

Please carefully review our certification FAQs and exam policies before scheduling your exam.

If you have any questions, please contact us here.

Certification Exam Details

Duration: 90 minutes

Price: $400

Certification level: Professional

Subject: AI Operations

Number of questions: 50

Prerequisites: Two to three years of operational experience working in a data center with NVIDIA hardware solutions. The candidate should be able to monitor and manage all the parts of a data center infrastructure in support of AI workloads.

Language: English

Validity: This certification is valid for two years from issuance. Recertification may be achieved by retaking the exam.

Credentials: Upon passing the exam, participants will receive a digital badge and optional certificate indicating the certification level and topic.

Exam Preparation

Topics Covered in the Exam

Topics covered in the exam include:

Base Command Manager for configuration, management, and troubleshooting
Slurm cluster administration
Kubernetes cluster administration
System management tools for troubleshooting and performance optimization

Candidate Audiences

MLOps engineers
DevOps engineers
Solution architects
System architects
AI Infrastructure engineers

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Exam Blueprint

The table below provides an overview of the topic areas covered in the certification exam and how much of the exam is focused on that subject.

Topics Areas	% of Exam	Topics Covered
Administration	36%	Administer Fleet Command Administer Slurm cluster Understand data center architecture for AI workloads Administer Base Command Manager (BCM) and cluster provisioning Administer Run.ai (potentially part of ACM) Configure MIG (for AI and HPC)
Workload Management	16%	Administer Kubernetes cluster Use system management tools to troubleshoot issues
Installation and Deployment	26%	Install and configure BCM Install and initialize Kubernetes on NVIDIA hosts using BCM Deploy containers from NGC Deploy cloud VMI containers Understand storage requirements for AI data centers Deploy DOCA services on DPU Arm
Troubleshooting and Optimization	20%	Troubleshoot docker Troubleshoot the fabric manager service for NVIDIA NVlink™/NVswitch™ systems Troubleshoot BCM Troubleshoot Magnum IO components Troubleshoot storage performance

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