NVIDIA-Certified Associate: AI Infrastructure and Operations (NCA-AIIO) Practice Exam

What the NVIDIA-Certified Associate exam covers

• Essential AI Knowledge278 questions
• AI Infrastructure292 questions
• AI Operations161 questions

Free NVIDIA-Certified Associate sample questions

A sample of 10 questions with answers and explanations. Sign up free to practice all 731.

1. Question 1Essential AI Knowledge

   Which describes the relationship between artificial intelligence, machine learning and deep learning?

   • ADeep learning is a subset of machine learning, which is a subset of artificial intelligenceCorrect
   • BMachine learning is a subset of deep learning, which is a subset of artificial intelligence
   • CArtificial intelligence is a subset of machine learning, which uses deep learning
   • DThe three are separate disciplines that do not overlap with one another
   ✓ Correct answer: A

   Artificial intelligence is the broad ambition of making machines behave intelligently, machine learning is the subset that learns patterns from data rather than following hand written rules, and deep learning is the subset of machine learning built on multi layer neural networks. Keeping the nesting straight matters because the infrastructure requirements differ sharply between them.

   Why the other options are wrong

   • BMachine learning is the broader of the two; deep learning is the subset within it.
   • CArtificial intelligence is the broadest term rather than a subset of machine learning.
   • DThe three overlap by definition rather than being separate disciplines.
2. Question 2Essential AI Knowledge

   Which describes object detection compared with image classification?

   • ADetection locates and identifies multiple objects, while classification labels the whole imageCorrect
   • BDetection labels the whole image, while classification locates individual objects
   • CDetection works on video only, while classification works on still images only
   • DDetection requires no training data, while classification requires labelled examples
   ✓ Correct answer: A

   The distinction matters because detection produces bounding boxes and is correspondingly more expensive both to label and to run. Choosing the simpler task where it suffices saves a great deal of effort. Both work on images and video, and both need labelled training data.

   Why the other options are wrong

   • BThe two are the other way round; detection is the one that locates objects.
   • CBoth tasks apply to still images and to video frames alike.
   • DDetection requires labelled training data just as classification does.
3. Question 3Essential AI Knowledge

   Which describes a residual or skip connection in a neural network?

   • AA path that carries a layer's input forward and adds it to the outputCorrect
   • BA path that removes a layer from the network once training finishes
   • CA path that sends gradients straight to the optimiser without a loss
   • DA path that connects two separate models into a single pipeline
   ✓ Correct answer: A

   Letting information bypass a block gives gradients a short route back to early layers, which is what made networks of a hundred layers trainable and remains standard in vision and transformer designs alike. It is a structural feature rather than a pruning step, an optimiser path or a model pipeline.

   Why the other options are wrong

   • BA path that removes a layer after training describes pruning instead.
   • CGradients reach the optimiser through the loss rather than by that path.
   • DConnecting two separate models into a pipeline is a composition.
4. Question 4Essential AI Knowledge

   Which describes the effect of raising the sampling temperature when generating text?

   • AOutputs become more varied and less predictable from one run to the nextCorrect
   • BOutputs become shorter because fewer tokens are permitted in total
   • COutputs are produced faster because fewer calculations are required
   • DOutputs are grounded more firmly in the retrieved source documents
   ✓ Correct answer: A

   Temperature flattens or sharpens the probability distribution the next unit is drawn from, so a low value gives repeatable and conservative text while a high value gives creative and sometimes incorrect text. Choosing it is a product decision. It does not change length, speed or how firmly an answer is grounded in sources.

   Why the other options are wrong

   • BOutputs become shorter only when the token limit permits fewer tokens.
   • COutputs are not produced faster; the calculations required are unchanged.
   • DGrounding in retrieved documents comes from retrieval, not sampling.
5. Question 5AI Infrastructure

   Which describes an accelerator's occupancy?

   • AHow fully the device's parallel execution resources are being usedCorrect
   • BHow much of the device's memory capacity has been allocated
   • CHow many separate users are sharing the device at one time
   • DHow many hours per day the device is powered on in the rack
   ✓ Correct answer: A

   A workload can allocate the whole device and still leave most of its capability idle if the work is too small or badly shaped, which is exactly what profiling reveals. Improving it usually means larger batches or better kernels. Memory allocation, user count and powered hours are other measures altogether.

   Why the other options are wrong

   • BHow much memory has been allocated is a capacity measurement.
   • CHow many users share the device is a multi tenancy question.
   • DHow many hours the device is powered on is a utilisation statistic.
6. Question 6AI Infrastructure

   Which describes remote direct memory access in a cluster network?

   • AOne node writes into another node's memory without involving its processorCorrect
   • BOne node reads a file from another node's local disk over a share
   • COne node borrows memory capacity from another node when it runs short
   • DOne node copies its entire memory contents to another for redundancy
   ✓ Correct answer: A

   Bypassing the operating system on both sides removes copies and interrupts, which cuts latency dramatically and frees processor cycles for useful work, and that is precisely what makes distributed training viable at scale. It is a transfer mechanism rather than file sharing, memory borrowing or mirroring.

   Why the other options are wrong

   • BReading a file from another node over a share is a file protocol.
   • CBorrowing memory capacity from another node is memory pooling.
   • DCopying entire memory contents for redundancy is a mirroring technique.
7. Question 7AI Infrastructure

   Which describes NVIDIA DALI in a data pipeline?

   • AA library that moves decoding and augmentation onto the acceleratorCorrect
   • BA library that implements the layers of a neural network model
   • CA service that stores datasets for an accelerated cluster
   • DA tool that converts trained models into optimised engines
   ✓ Correct answer: A

   When host threads cannot decode images fast enough, shifting that work to the device removes the bottleneck without adding servers, which is a common remedy for a starved training run. Neural network layers, dataset storage and inference compilation are the responsibilities of other components.

   Why the other options are wrong

   • BA library implementing network layers belongs to the framework.
   • CA service storing datasets for a cluster is a storage system.
   • DA tool converting models into optimised engines is TensorRT.
8. Question 8AI Infrastructure

   Which describes a bursting arrangement between owned and rented capacity?

   • AWork overflows to rented capacity when the owned cluster is saturatedCorrect
   • BWork always starts in the cloud and moves inward when capacity frees
   • CWork is split so half of every job runs in each environment
   • DWork is duplicated in both environments and the faster result kept
   ✓ Correct answer: A

   Keeping the owned cluster busy first and spilling the excess captures the economics of ownership without making users queue during a spike, provided the software stack and data access work in both places. The remaining descriptions waste capacity or split jobs in ways that would perform badly.

   Why the other options are wrong

   • BStarting in the cloud and moving inward inverts the intended economics.
   • CSplitting every job across two environments would perform very badly.
   • DDuplicating work in both environments wastes half of the capacity.
9. Question 9AI Operations

   Which describes saturation as a monitoring signal?

   • AHow close a resource is to the limit beyond which it will queue or failCorrect
   • BThe total number of requests the service has handled since it started
   • CThe proportion of requests that returned an error to the caller
   • DThe time taken by the slowest request in the observed period
   ✓ Correct answer: A

   It is the leading indicator among the core signals, because a resource approaching its ceiling predicts the latency and error increases that follow. Watching it buys time to act. Cumulative request counts, error proportions and slowest request times are traffic, error and latency measures respectively.

   Why the other options are wrong

   • BThe total number of requests handled is a traffic measure instead.
   • CThe proportion of requests returning an error is the error rate.
   • DThe time taken by the slowest request is a latency measure.
10. Question 10AI Operations

    Which describes an appropriate first action when a production inference service is failing?

    • ARestore service, using rollback if a recent change is the likely causeCorrect
    • BBegin a full root cause investigation before touching anything
    • CWait to see whether the problem resolves without intervention
    • DRetrain the model on more recent data as quickly as possible
    ✓ Correct answer: A

    Users are affected while the investigation proceeds, so recovery comes first and understanding follows once the pressure is off, which is exactly why rollback plans are prepared in advance. Investigating first prolongs the outage, waiting is not a response, and retraining takes far too long.

    Why the other options are wrong

    • BA full root cause investigation before restoring prolongs the outage.
    • CWaiting for a problem to resolve itself is not an incident response.
    • DRetraining the model takes far too long to serve as an immediate fix.

Who this NVIDIA-Certified Associate practice exam is for

This practice set is for anyone preparing for the NVIDIA-Certified Associate: AI Infrastructure and Operations (NCA-AIIO) exam at the foundational level - from first-time candidates building a foundation to experienced NVIDIA practitioners doing a final review before test day. If you learn best by working through realistic questions and reading why each answer is right or wrong, it is built for you.

How to use this NVIDIA-Certified Associate practice exam

1. Start with the free sample questions above to gauge your current baseline.
2. Read the full explanation on every question, including why each wrong option is wrong.
3. Track your weak domains and focus your study where you are losing the most marks.
4. Once you are scoring consistently well, take a timed, full-length mock exam.
5. Use your readiness score to decide when you are ready to book the real NVIDIA-Certified Associate exam.

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