NVIDIA NCA-GENM dumps - in .pdf

NCA-GENM pdf
  • Exam Code: NCA-GENM
  • Exam Name: NVIDIA Generative AI Multimodal
  • Updated: Sep 10, 2026
  • Q & A: 58 Questions and Answers
  • PDF Price: $59.99
  • Free Demo

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  • Exam Code: NCA-GENM
  • Exam Name: NVIDIA Generative AI Multimodal
  • Updated: Sep 10, 2026
  • Q & A: 58 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
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NVIDIA NCA-GENM dumps - Testing Engine

NCA-GENM Testing Engine
  • Exam Code: NCA-GENM
  • Exam Name: NVIDIA Generative AI Multimodal
  • Updated: Sep 10, 2026
  • Q & A: 58 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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NVIDIA NCA-GENM Exam Syllabus Topics:

SectionWeightObjectives
Experimentation25%- Experiment design and methodology
- Model training, fine-tuning, and evaluation
- Metrics and validation strategies for generative models
Data Analysis and Visualization10%- Interpretation of generative AI outputs
- Visualization techniques for model behavior and results
- Analyzing multimodal datasets and outputs
Software Development and Engineering15%- Best practices for building and maintaining systems
- Development workflows for generative AI applications
- Libraries, frameworks, and tools for multimodal AI
Core Machine Learning and AI Knowledge20%- Generative AI principles and techniques
- Fundamental concepts of machine learning and deep learning
- Neural network architectures relevant to multimodal systems
Trustworthy AI5%- Ethical considerations and responsible use
- Reliability, fairness, and safety in generative systems
- Robustness and error mitigation
Performance Optimization10%- Hardware acceleration with NVIDIA platforms
- Model efficiency and inference optimization
- Scalability and deployment considerations
Multimodal Data15%- Multimodal model architectures and integration
- Characteristics of text, image, and audio data
- Data preprocessing, fusion, and representation

NVIDIA Generative AI Multimodal Sample Questions:

Question 1

During the process of data cleansing, which of the following steps is NOT typically performed?

A. Identifying and handling missing values
B. Collecting additional data
C. Removing duplicates
D. Transforming data into a different format


Question 2

You are developing a GenAI-Multimodal system that uses data from various sources. What is one potential issue you need to consider in relation to bias in data?

A. Bias in data is not a concern for AI systems as they are designed to be neutral and objective.
B. Bias in data can only be addressed after the AI system has been deployed.
C. The data used to train the AI system may not be representative of the population it is intended to serve.
D. Bias in data is irrelevant as long as the AI system produces accurate predictions.


Question 3

What is a common method to reduce the computational cost of deep learning models during inference?

A. Adding more convolutional filters.
B. By replacing activation functions in some neurons with simpler ones.
C. Pruning weights or neurons.
D. Increasing the batch size.


Question 4

You have a dataset containing information about sales performance for different regions in the last ten years.
Which type of data visualization would be most appropriate to compare the sales performance across regions on a year-by-year basis?

A. Pie chart
B. Line chart
C. Bar chart
D. Scatter plot


Question 5

What does 'modality alignment' refer to?

A. Addressing challenges related to missing or incomplete information across different modalities.
B. Aligning different modalities within multimodal data to ensure meaningful connections and associations.
C. The process of integrating diverse data types such as text, images, audio, time series, and geospatial information.
D. The integration of pretrained models to perform custom tasks involving different types of data.


Solutions:

Question 1
Answer: B
Question 2
Answer: C
Question 3
Answer: C
Question 4
Answer: A
Question 5
Answer: B

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