NCA-AIIO study guide · 2026

The 3 NCA-AIIO domains, explained

3 domains and 22 official objectives. AI Infrastructure carries the most weight at 40%. Each guide explains what the domain covers, how its questions are framed and where candidates lose marks.

Start with Domain 2 See all domains
Questions
50
Time
60 minutes
Passing score
Not published
Outline
NCA-AIIO exam study guide (January 2026 edition, current)

Exam blueprint

Bar widths follow the official weights. Weight ranges are drawn at their midpoint.

  1. 1 38%
  2. 2 40%
  3. 3 22%
  1. 1 Essential AI Knowledge
  2. 2 AI Infrastructure
  3. 3 AI Operations

All 3 domains

22 official objectives 38–52 hrs suggested study

  1. Domain 01 38%

    Essential AI Knowledge

    This domain covers the AI fundamentals an infrastructure professional needs: how AI, machine learning and deep learning relate, why GPUs beat CPUs for parallel work, how training differs from inference, and where NVIDIA software and platforms fit in the AI lifecycle.

    Inside this domain

    • Describe the NVIDIA software stack used in an AI environment.
    • Compare and contrast training and inference architecture requirements and considerations.
    • Differentiate the concepts of AI, machine learning, and deep learning.
    • Explain the factors contributing to recent rapid improvements and adoption of AI.
    • and 4 more objectives

    Watch for CUDA is a framework

    Objectives
    8
    Questions est.
    ~19
    Study time est.
    14–18 hrs
  2. Domain 02 40%

    AI Infrastructure

    The largest NCA-AIIO domain covers the physical side of AI: choosing GPU hardware, scaling up and out, power and cooling, on-prem versus cloud, cluster and facility needs, AI networking with InfiniBand, Ethernet and NVLink, and the role of DPUs.

    Inside this domain

    • Identify hardware requirements for specific AI training task use cases.
    • Scale a GPU infrastructure for different use cases.
    • Identify key concepts and high-level specifications related to power and cooling requirements within a data center.
    • Articulate the key advantages, challenges, and considerations related to on-prem vs cloud infrastructures.
    • and 6 more objectives

    Watch for More GPUs per node

    Objectives
    10
    Questions est.
    ~20
    Study time est.
    16–22 hrs
  3. Domain 03 22%

    AI Operations

    This domain covers running AI infrastructure day to day: managing and monitoring the data center, scheduling jobs with Kubernetes and Slurm, tracking GPU health metrics, and sharing GPUs through MIG, vGPU and passthrough.

    Inside this domain

    • Describe AI data center management and monitoring essentials.
    • Describe AI cluster orchestration and job scheduling essentials.
    • Articulate the key measures and criteria related to monitoring GPUs.
    • Identify the key considerations for virtualizing accelerated infrastructure.

    Watch for nvidia-smi for the fleet

    Objectives
    4
    Questions est.
    ~11
    Study time est.
    8–12 hrs

Study the heaviest domains first

Marks follow weight. This order puts the most marks behind you first, across about 38–52 hrs of study.

  1. 2 AI Infrastructure 40% · 16–22 hrs
  2. 1 Essential AI Knowledge 38% · 14–18 hrs
  3. 3 AI Operations 22% · 8–12 hrs

Try one

Practice questionDomain 2: AI Infrastructure

A cloud provider hosts several AI tenants on shared GPU servers. Host CPUs spend significant cycles on virtual switching, encryption and firewall rules, and the security team wants these controls isolated from tenant operating systems. Which component best addresses both needs?

One trap from every domain

The answer that looks right, and the clue that gives it away.

  • Domain 1

    CUDA is a framework

    Clue The question asks what data scientists use to define and train models.

  • Domain 2

    More GPUs per node

    Clue Low utilization during cross-node communication.

  • Domain 3

    nvidia-smi for the fleet

    Clue The scenario mentions many nodes or dashboards.

Other Artificial Intelligence & Machine Learning certifications

Study guides for exams that overlap with NCA-AIIO.

Practise what you read

NCA-AIIO domains: common questions

How many domains are in the NCA-AIIO exam?

NCA-AIIO has 3 domains with 22 official objectives between them: Essential AI Knowledge, AI Infrastructure and AI Operations.

Which NCA-AIIO domain carries the most weight?

AI Infrastructure is the heaviest at 40%, followed by Essential AI Knowledge (38%). The lightest is AI Operations (22%). Weights come from NVIDIA's official outline.

What is the NCA-AIIO exam format?

Questions: 50. Time allowed: 60 minutes. Passing score: Not published.

How long should I study for NCA-AIIO?

Our planning estimate is 38–52 hrs across all domains, split by weight. It is an editorial estimate, not an official figure, so adjust it to your experience and to how you score on practice questions.

Where should I start?

Start with AI Infrastructure, because it carries the most marks, then work down by weight. Use the checklist on each domain page to confirm you can do what the domain asks before moving on.

Which outline is this guide based on?

This guide follows NCA-AIIO exam study guide (January 2026 edition, current), published by NVIDIA. It was last reviewed in October 2026.

Domain names, weights and objectives come from NVIDIA's official outline (NCA-AIIO exam study guide (January 2026 edition, current)). Question counts and study hours are editorial planning estimates, not official figures. Last reviewed October 2026.