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NCP-AIO: NVIDIA AI Operations Professional Certification
Rating: 3.6 out of 5(5 ratings)
102 students

NCP-AIO: NVIDIA AI Operations Professional Certification

Master NVIDIA AI cluster operations - BCM, Slurm, Kubernetes, Run:ai - with hands-on command-line practice
Created byAseem Mankotia
Last updated 10/2026
English
English [Auto],

What you'll learn

  • Prepare for the NVIDIA Certified Professional: AI Operations (NCP-AIO) exam with domain-by-domain, exam-focused coverage
  • Deploy and administer NVIDIA AI clusters with Base Command Manager, Slurm, Kubernetes and Run:ai
  • Manage multi-tenant workloads, resource allocation and NGC containers for inference and training
  • Troubleshoot NVIDIA AI infrastructure systematically under exam and production pressure

Course content

9 sections • 9 lectures • 2h 47m total length
  • Base Command Manager: Installation and Cluster Initialization18:29

Requirements

  • Comfort with the Linux command line and basic cluster/networking concepts; hands-on GPU access is helpful but not required

Description

This course contains the use of artificial intelligence.

Prepare for the NVIDIA Certified Professional: AI Operations (NCP-AIO) exam. This is a hands-on, command-line-first course built specifically for the professional-level credential that validates you can deploy, administer, and troubleshoot NVIDIA AI clusters in real production environments.

Exam facts, covered precisely: the NCP-AIO exam is 30 multiple-choice questions plus 3 hands-on lab exercises delivered in a single 120-minute online proctored session, at the professional (advanced) level. This course is structured to map directly onto all four official exam domains at their real weights: Installation and Deployment (31%), Administration (23%), Workload Management (23%), and Troubleshooting and Optimization (23%). No domain is skipped and study time follows the weighting.

What you will master, chapter by chapter:

  • Base Command Manager end to end: installation, cluster initialization, firmware, networking, and advanced day-two operations
  • Workload managers in depth: Slurm and Kubernetes running on BCM, plus Run:ai for shared AI infrastructure
  • Multi-tenant workload deployment for both inference and training pipelines
  • Resource allocation strategy and NGC container management
  • A systematic, repeatable approach to troubleshooting NVIDIA AI infrastructure under pressure
  • A complete exam-simulation chapter with a 120-minute time-management strategy for the combined MCQ and lab format

Every chapter includes real command-line practice so you build the operational muscle memory the exam actually tests, not just theory. This course is designed for AI infrastructure engineers, MLOps and platform engineers, and HPC administrators who run NVIDIA GPU clusters and want a recognized professional credential to prove it.

AI content disclosure: This course was produced with the assistance of artificial intelligence tools. Lecture narration is AI-voice generated, and lecture scripts, slides, and practice questions were drafted with AI assistance, then reviewed and curated by the instructor for technical accuracy and alignment with the official NCP-AIO exam guide.

Who this course is for:

  • AI infrastructure, MLOps and platform engineers and HPC administrators running NVIDIA GPU clusters who want the NCP-AIO credential