NVIDIA-Certified Professional

AI Networking

(NCP-AIN)

About This Certification
Exam Preparation
Exam Blueprint
Contact Us
Stay Informed

About This Certification
Exam Preparation
Exam Blueprint
Contact Us
Stay Informed

About This Certification

The NCP-AI Networking certification is an intermediate-level credential that validates a candidate’s ability to deploy and configure environments that leverage NVIDIA’s advanced networking technologies. The exam is online and proctored remotely, includes 70 to 75 questions, and has a 120-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.

To access the exam, you’ll need to create a Certiverse account.

Certification Exam Details

Duration: 120 minutes

Price: $400

Certification level: Professional

Subject: AI Networking

Number of questions: 70-75

Prerequisites: Two to three years of operational experience working in a data center with NVIDIA hardware solutions. The candidate should be able to deploy and manage NVIDIA AI networking 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:

AI Data Center Design and Optimization
NVIDIA Spectrum Networking
NVIDIA InfiniBand Networking
Kubernetes Integration
Troubleshooting Tools
Automation and Configuration

Candidate Audiences

Data center administrators
Infrastructure administrators
Network administrators
Network engineers
Storage administrators
System administrators
Solution architects

Certification Learning Path

InfiniBand Essentials

This self-paced course introduces IT professionals to the high-performance networking technologies that power modern HPC and AI data centers. The course covers the core concepts, architecture, benefits, and management fundamentals of InfiniBand, providing a strong foundation for exploring advanced high-speed interconnect technologies.

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InfiniBand Network Administration

This self-paced course is based on the InfiniBand specification and covers both theoretical and practical aspects. It is designed to meet the needs of anyone who installs, configures, manages, troubleshoots, or monitors InfiniBand fabrics.

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Cumulus Linux Essentials

Get started with NVIDIA Cumulus Linux in this self-paced introductory course. Covering the core pillars of open networking, you will learn to navigate the NVUE CLI, configure Layer 2 interfaces (L2, SVIs, VRR), and implement advanced routing protocols like FRR and BGP Unnumbered.

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Exam Study Guide

Review study guide

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.

Topic Areas	% of Exam	Topics Covered
AI Data Center Design and Optimization	5%	Describe an AI factory networking architecture and its components (e.g., GPUs, NVIDIA® BlueField®, scalable units, switches). Describe rail-optimized topologies for high-performance AI workloads. Describe GPU-to-GPU communications
NVIDIA Spectrum Networking	30%	Configure NVIDIA Spectrum-X switches for RDMA over Converged Ethernet (RoCE) to enable high-speed, low-latency communication. Enable and verify QoS, explicit congestion notification (ECN), and priority flow control (PFC), advanced features like adaptive routing, and telemetry Configure multi-tenancy Border Gateway Protocol Ethernet VPN (BGP-EVPN) to isolate tenant workloads. Use NVIDIA Air to simulate network environments and identify potential issues. Diagnose congestion or packet loss using in-band telemetry and NVIDIA What Just Happened® (WJH) services. Use NetQ for real-time network monitoring, including congestion detection and latency measurements. Install NVIDIA DOCA™. Configure NVIDIA SuperNIC™ functionality for advanced packet processing and congestion control.
NVIDIA InfiniBand Networking	30%	Perform initial configuration and provisioning, including high availability (HA). Configure partition keys (PKeys) to ensure secure multi-tenancy in InfiniBand networks. Configure QoS and adaptive routing to dynamically adjust paths based on congestion. Use UFM to monitor InfiniBand link status and bandwidth utilization.
Kubernetes Integration	5%	Deploy the NVIDIA Network Operator to manage RDMA interfaces and InfiniBand networks within Kubernetes clusters. Verify NVIDIA Network Operator functionality.
Troubleshooting Tools	20%	Use tools like cl-resource-query to check resource allocation in Spectrum-X environments. Use WJH services for real-time event analysis. Verify low-latency interconnects between GPUs, CPUs, and storage systems. Use UFM system health to diagnose InfiniBand issues Use commands like ib_write_lat, ib_write_bw, ibping, ibstat, ibdiagnet, ibnodes, and iblinkinfo to diagnose connectivity issues.
Automation and Configuration	10%	Manage Spectrum-X switch configurations through NVUE templates. Write Ansible playbooks to automate network setup tasks like VLAN creation or RoCE configuration.

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NVIDIA offers training and certification for professionals looking to enhance their skills and knowledge in the field of AI, accelerated computing, data science, advanced networking, graphics, simulation, and more.

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