NVIDIA NCA-AIIO Exam Study Material
NVIDIA-Certified Associate AI Infrastructure and Operations- 50 Questions & Answers
- Update Date : April 29, 2026
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Question 1
Which of the following statements correctly highlights a key difference between GPU and CPU architectures?
A. CPUs are optimized for parallel processing, making them better for AI workloads, while GPUs are designed for sequential tasksB. GPUs typically have higher clock speeds than CPUs, allowing them to process individual tasks faster
C. CPUs are specialized for graphical computations, whereas GPUs handle general-purpose computing
D. GPUs are optimized for parallel processing, with thousands of smaller cores, while CPUs have fewer, more powerful cores for sequential tasks
Question 2
Which two software components are directly involved in the life cycle of AI development anddeployment, particularly in model training and model serving? (Select two)
A. PrometheusB. MLflow
C. Airflow
D. Apache Spark
E. Kubeflow
Question 3
A retail company is considering using AI to enhance its operations. They want to improve customerexperience, optimize inventory management, and personalize marketing campaigns. Which AI usecase would be most impactful in achieving these goals?
A. AI-powered recommendation systems, which personalize product suggestions for customers based on their behaviorB. Natural language processing for automated customer support chatbots
C. AI-driven fraud detection to prevent unauthorized transactions
D. Image recognition for automatic labeling of products in warehouses
Question 4
Which of the following is a primary challenge when integrating AI into existing IT infrastructure?
A. Ensuring AI models have a user-friendly interfaceB. Scalability of the AI workloads
C. Finding AI tools that are compatible with existing hardware
D. Selecting the right cloud service provider
Question 5
A large manufacturing company is implementing an AI-based predictive maintenance system toreduce downtime and increase the efficiency of its production lines. The AI system must analyze datafrom thousands of sensors in real-time to predict equipment failures before they occur. However,during initial testing, the system fails to process the incoming data quickly enough, leading todelayed predictions and occasional missed failures. What would be the most effective strategy toenhance the system's real-time processing capabilities?
A. Reduce the number of sensors to decrease the amount of data the AI system must processB. Use a more complex AI model to enhance prediction accuracy
C. Implement edge computing to preprocess sensor data closer to the source before sending it to thecentral AI system
D. Increase the frequency of sensor data collection to provide more detailed inputs for the AI model