NVIDIA· Professional

NVIDIA-Certified Professional: AI Operations

NCP-AIO

Pass your certification on the first attempt with exam-realistic practice tests and detailed explanations

420+

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7

Testes Práticos

19

Hands-on labs

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Practice

7 Exam-realistic practice tests

420+ questions

Practice exam · NCP-AIOQ 1 / 65

Correct · explanation

Hands-on

Labs· 19

Browse all labs

# nca-aiio-resource-requests-limits · step 1

Step 1 Complete

grade ........... pass

intermediate40m

Kubernetes Resource Requests & Limits — Who Gets What, and Who Survives

# nca-aiio-gpu-operator-chain · step 1

Step 1 Complete

grade ........... pass

intermediate35m

Inside the NVIDIA GPU Operator — From Helm to Workload-Ready

intermediate40m

GPU Container Lifecycle: Build, Test, Ship, Rollback

intermediate35m

GPU Cost & Efficiency Audit

# NVML · health probe

$ pynvml.nvmlDeviceGetPids

rogue_pid ....... 2341

VRAM leak: 14.7 GB

remediation: SIGKILL → clean

GPU Health Checks + Auto-Remediation

intermediate40m

GPU Observability: From nvidia-smi to a Production Monitoring Stack

GPU Sharing: Streams, MPS, MIG, and the Real Cost of Contention

intermediate40m

Inference Serving Patterns: Dynamic Batching, Throughput, and the Triton Mental Model

intermediate35m

MLflow Experiment Tracking: From Single Run to Team Workflow

intermediate35m

Nsight Systems Profiling: Finding the Bottleneck That Costs You 40% of Your GPU

# determinism flags

$ torch.use_deterministic_…

seed ............ 42

cudnn.benchmark . False

reproducible .... TRUE

intermediate40m

Reproducible Training: The Flags, The Cost, The Artifacts

vLLM Production Serving: PagedAttention, Continuous Batching, Prefix Caching

intermediate40m

NVIDIA GPU Operator on k3s: Single-Node Kubernetes for GPU Workloads

# nca-aiio-priority-preemption · step 1

Step 1 Complete

grade ........... pass

intermediate35m

PriorityClass & Preemption — Who Survives the GPU Squeeze

intermediate35m

Persistent Storage for AI Workloads — PVCs, StorageClass & the Checkpoint Pattern

# nca-aiio-workload-controllers · step 1

Step 1 Complete

grade ........... pass

intermediate35m

Workload Controllers — Deployment, StatefulSet, DaemonSet for AI

intermediate35m

Rolling Updates, Rollback & Blue-Green for AI Inference

intermediate40m

Stuck-Pending Triage Day — Diagnose Any GPU Pod That Won't Run

intermediate35m

Multi-GPU-Type Targeting — nodeSelector, nodeAffinity & Tolerations

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