Easy — NCA-AIIO Practice Quiz

Question 1

A retail analytics team wants to build a model that predicts whether a customer will churn based on historical account data. They have three years of records where each customer is already tagged as 'churned' or 'retained'. A data scientist argues this is a classic supervised learning problem. Which characteristic of the team's dataset most directly justifies classifying this as supervised learning?

Accepted Answer

The dataset contains labeled examples with known churn outcomes used to train the model to map inputs to correct outputs

Answer

The dataset is large enough to require GPU acceleration for training

Answer

The model must group customers into clusters without any predefined categories

Answer

The model learns by receiving rewards and penalties as it interacts with a live environment

Question 2

A new data scientist on your team is confused about the NVIDIA software stack. They ask which component provides the core programming interface and libraries that allow AI frameworks like PyTorch to execute general-purpose parallel computations directly on the GPU. Which component should you point them to?

Accepted Answer

CUDA — the parallel computing platform and programming model for GPUs

Answer

Triton Inference Server — for deploying trained models in production

Answer

NGC — a catalog of containers and pretrained models

Answer

NVIDIA AI Enterprise — a licensing and support subscription tier

Question 3

A junior analyst on your team is confused about terminology after a project kickoff. The team is building a system that automatically classifies medical images using a multi-layer neural network that learns features directly from raw pixel data without manual feature engineering. The analyst asks how this technique relates to the broader fields of artificial intelligence (AI) and machine learning (ML). Which statement correctly describes the relationship?

Accepted Answer

Deep learning is a subset of machine learning, which is itself a subset of artificial intelligence.

Answer

Machine learning is a subset of deep learning, which is a broader field than artificial intelligence.

Answer

Artificial intelligence, machine learning, and deep learning are three independent fields with no overlap.

Answer

Artificial intelligence is a subset of deep learning that only applies to neural networks with many layers.

Question 4

A large online retailer wants to automatically generate unique, natural-language product descriptions for millions of catalog items based on structured attributes like brand, color, and material. The team wants to fine-tune an existing foundation model rather than build one from scratch. Which category of AI technology is the most appropriate fit for this business requirement?

Accepted Answer

A generative large language model (LLM)

Answer

A classical linear regression model

Answer

A convolutional neural network (CNN) for image classification

Answer

A k-means clustering algorithm

Question 5

A data science team has spent three weeks running a workload on a GPU cluster where a neural network repeatedly processes a large labeled dataset, adjusting its internal weights after each pass to minimize prediction errors. A separate team now wants to take the resulting model and deploy it so a customer-facing app can return predictions on individual new inputs in real time. Which statement best characterizes these two phases?

Accepted Answer

The first phase is training, which is compute-intensive and updates model weights; the second phase is inference, which uses the fixed trained model to generate predictions on new data.

Answer

The first phase is inference because it repeatedly processes data; the second phase is training because it serves live users.

Answer

Both phases are training, since any use of a GPU with a neural network involves updating weights.

Answer

The first phase is fine-tuning and the second phase is quantization, which are the only two stages in a model lifecycle.