NVIDIA NCP-AAI Exam Details & Actual Exam Questions

  • Exam Code/Number: NCP-AAI
  • Exam Name/Title: Agentic AI
  • Certification Provider: NVIDIA
  • Corresponding Certification: NVIDIA-Certified Professional
  • Exam Questions: 123
  • Updated On: Jul,13 2026
  • Certification Level: Professional

NVIDIA Agentic AI Exam Questions

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NVIDIA NCP-AAI Exam Overview:

Certification Vendor:NVIDIA
Exam Name:NVIDIA Certified Professional: Agentic AI
Exam Number:NCP-AAI
Related Certifications:NVIDIA Certified Professional: Generative AI LLMs
Exam Duration:120 minutes
Passing Score:Not officially disclosed (commonly referenced ~70%)
Exam Price:$200 USD
Certificate Validity Period:2 years
Exam Format:Multiple Choice, Multiple Response, Scenario-based
Real Exam Qty:60–70
Available Languages:English
Sample Questions:NVIDIA NCP-AAI Sample Questions
Exam Way:Online, remotely proctored
Pre Condition:Recommended: 1–2 years experience in AI/ML roles, familiarity with LLM APIs, agent frameworks, and production AI systems
Official Syllabus URL:https://www.nvidia.com/en-us/learn/certification/agentic-ai-professional/

NVIDIA NCP-AAI Exam Syllabus Topics:

SectionWeightObjectives
Evaluation and Tuning13%- Performance evaluation
  • 1. A/B testing and failure analysis
    • 2. Benchmarking agent workflows
      Deployment and Scaling13%- Production deployment of agent systems
      • 1. Containerization and scaling strategies
        • 2. Latency and GPU optimization
          • 3. NVIDIA NIM microservices
            NVIDIA Platform Implementation7%- NVIDIA ecosystem tools
            • 1. TensorRT-LLM optimization
              • 2. NVIDIA NIM inference services
                • 3. NVIDIA Blueprints (AI-Q)
                  Agent Development15%- Implementation of agent systems
                  • 1. Tool integration and function calling
                    • 2. Guardrails (Colang 2.0)
                      • 3. NVIDIA NeMo Agent Toolkit usage
                        Knowledge Integration10%- Retrieval-Augmented Generation (RAG)
                        • 1. Vector database integration
                          • 2. RAG pipeline design
                            Agent Architecture and Design15%- Agent design patterns and reasoning frameworks
                            • 1. ReAct and Reflexion patterns
                              • 2. Multi-agent orchestration models
                                Cognition, Planning, and Memory10%- Reasoning and memory systems
                                • 1. Task decomposition and planning
                                  • 2. Short-term and long-term memory
                                    Safety, Ethics, and Human Interaction15%- Responsible AI design
                                    • 1. Auditability and compliance controls
                                      • 2. Bias mitigation and governance
                                        • 3. Human-in-the-loop (HITL) systems


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