1
Agent Architecture and Design
Foundational structuring and design of agentic AI systems, focusing on how agents interact, reason, and communicate within their environments.
15%of the exam
NVIDIAProfessional
NVIDIA-Certified Professional:Agentic AI
Validates the ability to architect, develop, deploy, and govern advanced agentic AI solutions, with a focus on multi-agent interaction, distributed reasoning, scalability, and ethical safeguards.
What this certification assesses
The ten topic areas NVIDIA publishes for this exam, in the order its certification page and study guide list them.
2
Agent Development
Practical building, integration, and enhancement of agents.
15%of the exam
3
Evaluation and Tuning
Measuring, comparing, and optimizing agent performance.
13%of the exam
4
Deployment and Scaling
Operationalizing and scaling agentic systems.
13%of the exam
5
Cognition, Planning, and Memory
Core cognitive processes underlying intelligent agent behavior, including reasoning strategies, decision-making, and memory management.
10%of the exam
6
Knowledge Integration and Data Handling
Integration of external knowledge and the management of diverse data types.
10%of the exam
7
NVIDIA Platform Implementation
Leveraging NVIDIA's AI hardware and software platforms for agentic AI systems.
7%of the exam
8
Run, Monitor, and Maintain
Ongoing operation, monitoring, and maintenance of agentic systems post-deployment.
7%of the exam
9
Safety, Ethics, and Compliance
Principles and practices that ensure agentic AI systems operate responsibly, uphold ethical standards, and comply with legal and regulatory frameworks.
5%of the exam
10
Human-AI Interaction and Oversight
The design and implementation of systems that facilitate effective human oversight and interaction with agents.
5%of the exam
Topic areas is NVIDIA's own term for these ten, and the titles and descriptions are its own; the numbers beside them are those its study guide gives the objectives under each. NVIDIA weights the topic areas twice, and its certification page and study guide disagree on two of them: Deployment and Scaling (13% on the page, 5% in the guide) and Run, Monitor, and Maintain (5% and 7%). The weights shown take the higher figure of each, the one combination of NVIDIA's numbers that adds up to 100%. The blueprint itself, with every objective under these sections, is in Official references.
Exam overview
Everything NVIDIA publishes about the assessment, read from the certification page and the exam study guide. Follow the sources for the authoritative version of any of it.
- Professional
- Level
- 60–70
- Questions
- 120 minutes
- Duration
- NCP-AAI
- Exam code
- English
- Language
Published detail
- Delivery
- Online and remotely proctored
- Registration fee
- $200 USD
- Validity
- 2 years from issuance
- Recertification
- Retake the exam
- Prerequisites
- 1–2 years of experience in AI/ML roles and hands-on work with production-level agentic AI projects, plus the knowledge and experience the certification page lists under Prerequisites
- Candidate audiences
- Software developers, software engineers, solutions architects, machine learning engineers, data scientists, AI strategists, and AI specialists
NVIDIA publishes no numeric passing score, no scoring model, and no test provider for this exam in particular, and its certification page and study guide give experience recommendations that cannot be reconciled — so none of those appears above. That page currently shows both a registration control and a “Coming soon” label, so this page does not state whether the exam can be taken today.
Based on NVIDIA's NCP-AAI exam study guide.
Who this certification is for
Our reading of who this certification is most relevant to. This framing is editorial — not something the vendor publishes.
- Solution architects
- Architects and senior engineers designing production agentic AI systems, which is where the exam puts architecture, deployment, and governance.
- AI/ML engineers
- Engineers responsible for evaluation, deployment, observability, and NVIDIA platform integration.
- Certification candidates
- Engineers preparing for NCP-AAI.
These groups are editorial. The experience the vendor actually recommends for the exam is a published fact, and it is in Exam overview.
Official references
Primary sources for everything on this page. Follow them for the authoritative version of any certification fact.
- Certification overview (opens in a new tab)The official page for the credential: exam code, length, fee, question range, prerequisites, validity, and the topic areas.
- Agentic AI exam study guide (opens in a new tab)NVIDIA's study guide PDF: the detailed topic structure, the job description, and its own recommended qualifications.
- Certification catalogue and FAQ (opens in a new tab)NVIDIA's program-wide pages: the catalogue entry, registration policy, scoring policy, and how credentials are delivered.
agentic-system.design is an independent learning guide. It is not affiliated with, endorsed by, or sponsored by NVIDIA, and it is not an official NVIDIA study guide. NVIDIA, NVIDIA-Certified Professional: Agentic AI, and the certification badge shown on this page are trademarks of NVIDIA Corporation, reproduced unaltered to identify the certification this page covers.
Study guide
Study for the NVIDIA-Certified Professional: Agentic AI exam
The guide follows this blueprint section by section, one decision per bite. Read it in order to prepare, or open a single bite later as a reference.
- Guide version
- October 2026
- Cost
- Free, no account
- Progress
- Stays in your browser