NVIDIA NCA-GENM : NVIDIA Generative AI Multimodal

NCA-GENM pass collection

Exam Code: NCA-GENM

Exam Name: NVIDIA Generative AI Multimodal

Updated: Oct 13, 2026

Q & A: 58 Questions and Answers

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NVIDIA NCA-GENM Exam Syllabus Topics:

SectionWeightObjectives
Data Analysis & Visualization10%- Visualization techniques for multimodal data
- Data preprocessing and feature engineering
Performance Optimization10%- Monitoring and improving system efficiency
- Techniques for optimizing AI performance
Multimodal Data15%- Handling and integrating text, image, and audio data
- Applications and use cases
Core ML & AI Knowledge20%- Basic concepts and terminology
- Key algorithms and techniques
Experimentation25%- A/B testing
- Experimental design
- Hypothesis testing
- Model evaluation and comparison
Software Development & Engineering15%- Integration and deployment of multimodal AI systems
- Python libraries for multimodal AI
Trustworthy AI5%- Ethical considerations in AI development
- Ensuring fairness and transparency

NVIDIA Generative AI Multimodal Sample Questions:

Question #1

Which metric is commonly used for evaluating Automatic Speech Recognition (ASR) models?

  • A. F1 Score
  • B. Word Error Rate (WER)
  • C. CTC Loss
  • D. Mean Opinion Score (MOS)
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #2

You are evaluating the performance of an AI model for facial recognition. What is an important consideration when evaluating the model for bias?

  • A. The model's compatibility with different operating systems.
  • B. The model's processing speed in recognizing faces of different races.
  • C. The model's ability to recognize various facial expressions.
  • D. The model's accuracy in recognizing individuals of different races.
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Correct Answer: D  🗳️

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Question #3

In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?

  • A. Support vector machine (SVM)
  • B. K-means clustering
  • C. Decision tree
  • D. Generative adversarial network (GAN)
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Correct Answer: D  🗳️

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Question #4

Which of the following best describes the role of machine learning in handling multimodal data?

  • A. To enable models to learn from and interpret diverse data types.
  • B. To reduce the amount of data needed for accurate predictions.
  • C. To eliminate the need for human intervention in data analysis.
  • D. To focus on textual data analysis.
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Correct Answer: A  🗳️

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Question #5

Which of the following best describes the purpose of GAN (Generative Adversarial Networks)?

  • A. To optimize search algorithms for faster data retrieval.
  • B. To produce new data that is similar to the training data.
  • C. To optimize decision-making processes based on historical data.
  • D. To classify and categorize data based on patterns and features.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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