NVIDIA-Certified Professional # Agentic AI (NCP-AAI) [Register for Exam](https://www.certiverse.com/#/checkout/nvidia/store-exam/NCP-AAI) (Coming soon) ## About This Certification The Agentic AI LLMs professional certification is an intermediate-level credential that validates a candidate’s ability to architect, develop, deploy, and govern advanced agentic AI solutions, with a focus on multi-agent interaction, distributed reasoning, scalability, and ethical safeguards. The exam is online and proctored remotely, includes 60–70 questions, and has a 120-minute time limit. Please carefully review our [certification FAQs and exam policies](https://www.nvidia.com/en-us/learn/certification/#faq) before scheduling your exam. If you have any questions, please contact us [here](mailto:educert@nvidia.com). *Important Note: To access the exam, you’ll need to create a Certiverse account.* #### Certification Exam Details **Duration:** 120 minutes **Price:** $200 **Certification level:** Professional **Subject:** Agentic AI **Number of questions:** 60–70 **Prerequisites:** 1–2 years of experience in AI/ML roles and hands-on work with production-level agentic AI projects. Strong knowledge of agent development, architecture, orchestration, multi-agent frameworks, and the integration of tools and models across various platforms. Experience with evaluation, observability, deployment, user interface design, reliability guardrails, and rapid prototyping platforms is also essential for ensuring robust and scalable agentic AI solutions. **Language:** English **Validity:** This certification is valid for two years from issuance. Recertification may be achieved by retaking the exam. **Credentials:** Upon passing the exam, participants will receive a digital badge and optional certificate indicating the certification level and topic. ## Exam Preparation ### Topics Covered in the Exam * **Agent Design and Cognition**: Architect agents, apply reasoning and planning, manage memory, and coordinate multi-agent workflows. * **Knowledge Integration and Agent Development**: Implement retrieval pipelines, handle data, engineer prompts, and build multimodal, reliable agents. * **NVIDIA Platform Implementation and Deployment**: Use NVIDIA tools to optimize inference, deploy at scale, and manage production workflows. * **Evaluation, Monitoring, and Maintenance**: Benchmark and tune performance, monitor live systems, troubleshoot issues, and ensure continuous improvement. * **Human, Ethical, and Compliance Considerations**: Design human-in-the-loop systems, enforce safety and compliance guardrails, and uphold responsible AI practices. ### Candidate Audiences * Software developers * Software engineers * Solutions architects * Machine learning engineers * Data scientists * AI strategists * AI specialists ## Certification Learning Path Here’s the recommended training to prepare for this certification exam. [Self-Paced ### Building RAG Agents With LLMs $90 8 Hours Course certificate available Also offered as an instructor-led workshop.](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-15+V1) [Self-Paced ### Evaluating RAG and Semantic Search Systems $30 3 Hours](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-32+V1) [Self-Paced ### Building Agentic AI Applications With LLMs $90 8 Hours Course certificate available Also offered as an instructor-led workshop.](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-41+V1) [Instructor-Led ### Adding New Knowledge to LLMs $500 8 Hours Course certificate available](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-FX-26+V1) [Self-Paced ### Introduction to Deploying RAG Pipelines for Production at Scale $90 8 Hours Course certificate available Also offered as an instructor-led workshop.](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-19+V1) ## Exam Blueprint The table below provides an overview of the topic areas covered in the certification exam and how much of the exam is focused on that subject. | Topic Areas | % of Exam | Topics Covered | | --- | --- | --- | | **Agent Architecture and Design** | 15% | Foundational structuring and design of agentic AI systems, focusing on how agents interact, reason, and communicate within their environments | | **Agent Development** | 15% | Practical building, integration, and enhancement of agents | | **Evaluation and Tuning** | 13% | Measuring, comparing, and optimizing agent performance | | **Deployment and Scaling** | 13% | Operationalizing and scaling agentic systems | | **Cognition, Planning, and Memory** | 10% | Core cognitive processes underlying intelligent agent behavior, including reasoning strategies, decision-making, and memory management | | **Knowledge Integration and Data Handling** | 10% | Integration of external knowledge and the management of diverse data types | | **NVIDIA Platform Implementation** | 7% | Leveraging NVIDIA’s AI hardware and software platforms for agentic AI systems | | **Run, Monitor, and Maintain** | 5% | Ongoing operation, monitoring, and maintenance of agentic systems post-deployment | | **Safety, Ethics, and Compliance** | 5% | Principles and practices that ensure agentic AI systems operate responsibly, uphold ethical standards, and comply with legal and regulatory frameworks | | **Human-AI Interaction and Oversight** | 5% | The design and implementation of systems that facilitate effective human oversight and interaction with agents | ## Exam Study Guide Review [study guide](https://nvdam.widen.net/s/zvkhwfqllc/nvt-study-guide-new-agentic-ai-cert-exam-4230000) ### Get Certified Register now to take the next step in your career with an industry-recognized certification. 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