NVIDIA NCP-AAI study guide
NVIDIA NCP-AAI · Work through your exam, one topic at a time.
The NVIDIA-Certified Professional Agentic AI (NCP-AAI) is a professional-level credential in NVIDIA's certification program. NVIDIA describes it as demonstrating the ability to build and govern advanced agentic AI solutions with multi-agent interaction, scalability, and ethical safeguards. It sits alongside other professional exams such as NCP-GENL (Generative AI LLMs) and NCP-AII (AI Infrastructure), each listed at 200 with a 2-hour duration. The exam is aimed at practitioners who design, scale, and govern agentic systems rather than at candidates seeking foundational knowledge; NVIDIA's associate-level credentials (for example NCA-GENL or NCA-AMAD) cover entry-level understanding at 125 and 1 hour. Topics on this exam: Agentic AI solution design and multi-agent interaction, Scalability of agentic AI solutions, Ethical safeguards and governance of agentic AI, and Building and deploying advanced agentic AI solutions. The NVIDIA NCP-AAI study guide has 4 sections and about 1,401 words.
01Agentic AI Solution Design and Multi-Agent Interaction
Domain 1 - Agentic AI solution design and multi-agent interaction. The exam tests whether you can pick an agent topology, define tool and message contracts, and run an interaction loop that terminates reliably instead of looping or drifting.
360 words, about 2 min02Scalability of Agentic AI Solutions
Domain 2 - Scalability of agentic AI solutions. This domain tests how you keep latency and cost predictable when one user request expands into dozens of model and tool calls, and how you map that load onto NVIDIA serving infrastructure.
357 words, about 2 min03Ethical Safeguards and Governance of Agentic AI
Domain 3 - Ethical safeguards and governance of agentic AI. The exam tests controls for excessive agency, indirect prompt injection, data leakage, and accountability when agents act on real systems with real credentials.
339 words, about 2 min04Building and Deploying Advanced Agentic AI Solutions
Domain 4 - Building and deploying advanced agentic AI solutions. This domain tests the full lifecycle: evaluation-driven development, customization, production rollout, and monitoring of agents rather than single prompts.
345 words, about 2 min