NVIDIA NCA-GENL: Generative AI LLMs Practice Tests

About this course

This course contains the use of artificial intelligence.

Knowing the names of LLM tools is only the beginning. You also need to decide whether a problem comes from the data, retrieval, model behavior, evaluation or application code. These 320 original English questions help you practice those decisions for the NVIDIA-Certified Associate: Generative AI LLMs (NCA-GENL).

The course follows the five domains displayed on NVIDIA's certification page checked on October 11, 2026: Core Machine Learning and AI Knowledge, Data Analysis, Experimentation, Software Development, and Trustworthy AI. It targets the Associate LLM credential.

A focused path to mixed practice

Core ML, Embeddings and Prompting — 65 questions: feature and split choices, token and vector representations, prompt constraints and evidence-based RAG.Data Analysis and Trustworthy AI — 40 questions: interpreting metrics and charts, checking confounding and subgroup evidence, privacy, consent and layered controls.

Training, Feedback and Experiments — 55 questions: dataset preparation, fine-tuning, human preferences, reproducible comparisons and benchmark failure analysis.

LLM Applications and Python — 60 questions: model serving, component selection, monitoring, software boundaries and short numerical Python exercises.

Two separate mixed mocks — 50 questions each: complete each in 60 minutes, then use the feedback to examine why alternatives fail under the stated conditions.

Each question includes an answer, feedback for every option, an overall explanation and a focused study suggestion. Scenarios distinguish similar concepts: a high score can hide subgroup errors; a model file can fit while runtime memory fails; a citation can exist without supporting a claim.

How to use the questions

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