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NCA-GENL Generative AI LLM professional (NCA-GENL) - Nvidia Exam Questions

Last updated on July 22, 2026

97% Exam Compliance
95 Total Questions
1
Question
In the context of machine learning model deployment, how can Docker be utilized to enhance the process?
Options
A To directly increase the accuracy of machine learning models.
B To reduce the computational resources needed for training models.
C To provide a consistent environment for model training and inference.
D To automatically generate features for machine learning models.
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2
Question
Which model deployment framework is used to deploy an NLP project, especially for high- performance inference in production environments?
Options
A NVIDIA Triton
B NeMo
C HuggingFace
D NVIDIA DeepStream
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3
Question
When implementing data parallel training, which of the following considerations needs to be taken into account?
Options
A The model weights are kept independent for as long as possible increasing the model exploration.
B A master-worker method for syncing the weights across different processes is desirable due to its scalability.
C A ring all-reduce is an efficient algorithm for syncing the weights across different processes/devices.
D The model weights are synced across all processes/devices only at the end of every epoch.
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4
Question
What is the correct order of steps in an ML project?
Options
A Data collection, Data preprocessing, Model training, Model evaluation
B Data preprocessing, Data collection, Model training, Model evaluation
C Model evaluation, Data collection, Data preprocessing, Model training
D Model evaluation, Data preprocessing, Model training, Data collection
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5
Question
What do we usually refer to as generative AI?
Options
A A branch of artificial intelligence that focuses on analyzing and interpreting existing data.
B A branch of artificial intelligence that focuses on improving the efficiency of existing models.
C A branch of artificial intelligence that focuses on auto generation of models for classification.
D A branch of artificial intelligence that focuses on creating models that can generate new and original data.
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