NVIDIA NCP-AAI - Agentic AI Exam

Question #1 (Topic: Topic 1, Agent Architecture and Design )
When designing tool integration for an agent that needs to perform mathematical calculations, web searches, and API calls, which architecture pattern provides the most scalable and maintainable approach?
A. External tool services with manual configuration for each agent instance B. Microservice-based tool architecture with standardized interfaces C. Monolithic tool handler with conditional logic for different tool types D. Embedded tool functions within the main agent code
Answer: B
Question #2 (Topic: Topic 1, Agent Architecture and Design )
A company is deploying an AI-powered customer support agent that integrates external APIs and handles a wide range of customer inputs dynamically.
Which of the following strategies are appropriate when designing an AI agent for dynamic conversation management and external system interaction? (Choose two.)
A. Integrating a feedback loop from user interactions to iteratively improve agent behavior. B. Using rule-based logic as the primary framework to maintain consistency in agent decisions. C. Implementing retry logic for API failures to ensure robustness in external communications. D. Preferring hardcoded responses for frequent queries to deliver reliable and low-latency answers.
Answer: AC
Question #3 (Topic: Topic 1, Agent Architecture and Design )
In the context of agent development, how does an autonomous agent differ from a predefined workflow when applied to complex enterprise tasks?
A. Agents optimize for execution speed under fixed input-output mappings, while workflows prioritize goal alignment through adaptive reasoning and memory mechanisms. B. Workflows provide deterministic task sequencing with conditional branching, while agents adapt decisions dynamically based on goals, context, and environment feedback. C. Workflows emphasize parallelism and distributed coordination of processes, while agents emphasize serialization and isolated problem solving.
Answer: B
Question #4 (Topic: Topic 1, Agent Architecture and Design )
A Lead AI Architect at a global financial institution is designing a multi-agent fraud detection system using an agentic AI framework. The system must operate in real time, with distinct agents working collaboratively to monitor and analyze transactional patterns across accounts, retain and share contextual information over time, and escalate suspicious behaviors to a human fraud analyst when needed.
Which architectural approach enables intelligent specialization, shared memory, and inter-agent coordination in a dynamic and evolving threat environment?
A. Design a modular multi-agent system where individual agents collaborate asynchronously using shared memory and structured messaging. B. Design a multi-agent system where individual agents collaborate synchronously using shared memory and structured messaging. C. Design a centralized rule-based service that checks all transactions against static fraud indicators and sends alerts when thresholds are exceeded. D. Design an agentic workflow where each agent acts independently on isolated data slices with no inter-agent communication to reduce latency and model complexity. E. Design monolithic LLM-based agents that handle all fraud detection tasks within a single loop, without modular roles or multi-agent coordination.
Answer: A
Question #5 (Topic: Topic 1, Agent Architecture and Design )
When designing complex agentic workflows that include both sequential and parallel task execution, which orchestration pattern offers the greatest flexibility?
A. Graph-based workflow orchestration incorporating conditional branches B. Linear pipeline orchestration with a fixed task sequence C. Event-driven orchestration that triggers tasks reactively, in series or in parallel
Answer: A
Download Exam
Page: 1 / 25
Total 121 questions