Free NVIDIA NCA-GENL Exam Questions

Become NVIDIA Certified with updated NCA-GENL exam questions and correct answers

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Total 395 Questions | Updated On: Mar 06, 2026

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Question 1

What is the purpose of the NVIDIA NeMo Toolkit?

A : NeMo focuses on the morphology of a language by studying its words, and how they are formed.

B : NeMo helps researchers to develop models that trade-off size with minimum loss impact.

C : NeMo facilitates the creation of models for speech recognition and natural language understanding.

D : NeMo helps researchers develop state-of-the-art models for computer vision based on convolutions.

Answer: C

Question 2

Which of the following prompt engineering techniques is most effective for improving an LLM's performance on multi-step reasoning tasks?

A : Retrieval-augmented generation without context

B : Few-shot prompting with unrelated examples.

C : Zero-shot prompting with detailed task descriptions.

D : Chain-of-thought prompting with explicit intermediate steps.

Answer: D

Question 3

When fine-tuning an LLM for a specific application, why is it essential to perform exploratory data analysis (EDA) on the new training dataset?

A : To uncover patterns and anomalies in the dataset

B : To select the appropriate learning rate for the model

C : To assess the computing resources required for fine-tuning

D : To determine the optimum number of layers in the neural network

Answer: A

Question 4

You have access to training data but no access to test data. What evaluation method can you use to assess the performance of your AI model?

A : Cross-validation

B : Randomized controlled trial

C : Average entropy approximation

D : Greedy decoding

Answer: A

Question 5

What is Retrieval Augmented Generation (RAG)?

A : RAG is an architecture used to optimize the output of an LLM by retraining the model with domain-specific data.

B : RAG is a methodology that combines an information retrieval component with a response generator.

C : RAG is a method for manipulating and generating text-based data using Transformer-based LLMs.

D : RAG is a technique used to fine-tune pre-trained LLMs for improved performance.

Answer: B

Page: 1 / 79

Total 395 Questions | Updated On: Mar 06, 2026

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