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NVIDIA NCA-AIIO Study Guide
Home
Exam Overview
Exam Guide & Study Strategy
Domain Blueprint
Domain 1 — Essential AI Knowledge (38%)
1.1 NVIDIA Software Stack
1.2 Training vs Inference
1.3 AI vs ML vs DL
1.4 AI Adoption Drivers
1.5 AI Use Cases and Industries
1.6 NVIDIA Solutions: Purpose and Use Cases
1.7 AI Development and Deployment Lifecycle
1.8 GPU vs CPU Architecture
Domain 2 — AI Infrastructure (40%)
2.1 Hardware Requirements for AI Training
2.2 Scaling GPU Infrastructure
2.3 Power and Cooling Requirements
2.4 On-Premises vs Cloud
2.5 Cluster Components
2.6 Facility Requirements
2.7 Networking Requirements for AI Workloads
2.8 Data Center Networking Protocols
2.9 High-Speed Network Options
2.10 DPU Purpose and Benefits
Domain 3 — AI Operations (22%)
3.1 AI Data Center Management and Monitoring
3.2 Cluster Orchestration and Job Scheduling
3.3 GPU Monitoring Key Measures
3.4 Virtualizing Accelerated Infrastructure
NVIDIA Portfolio Reference
GPU Families
Superchips
DGX Systems
Networking Hardware
Software Stack
Field Notes
Sizing a First AI Cluster
Lessons Learned
Practice & Glossary
Glossary
Flashcards
Self-Quiz
NVIDIA Cert Page
Exam Overview
Everything you need before opening the first study section.
Table of contents
Exam Guide & Study Strategy
Domain Blueprint