NVIDIA : NCA-GENM Questions & Answers
Updated: Oct 08, 2026
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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Analysis and Visualization | 10% | - Visualization techniques for model behavior and results - Analyzing multimodal datasets and outputs - Interpretation of generative AI outputs |
| Topic 2: Core Machine Learning and AI Knowledge | 20% | - Fundamental concepts of machine learning and deep learning - Neural network architectures relevant to multimodal systems - Generative AI principles and techniques |
| Topic 3: Software Development and Engineering | 15% | - Development workflows for generative AI applications - Libraries, frameworks, and tools for multimodal AI - Best practices for building and maintaining systems |
| Topic 4: Performance Optimization | 10% | - Hardware acceleration with NVIDIA platforms - Scalability and deployment considerations - Model efficiency and inference optimization |
| Topic 5: Experimentation | 25% | - Model training, fine-tuning, and evaluation - Experiment design and methodology - Metrics and validation strategies for generative models |
| Topic 6: Trustworthy AI | 5% | - Ethical considerations and responsible use - Reliability, fairness, and safety in generative systems - Robustness and error mitigation |
| Topic 7: Multimodal Data | 15% | - Characteristics of text, image, and audio data - Multimodal model architectures and integration - Data preprocessing, fusion, and representation |
NVIDIA Generative AI Multimodal Sample Questions:
For building a zero-shot image classification pipeline, what could be a crucial step in the process?
- A. Manually labeling each image in the dataset for precise classification.
- B. Using a model like CLIP for encoding both images and their textual descriptions into a shared representation space for comparison.
- C. Focusing on enhancing the resolution and quality of images before classification.
- D. Designing an algorithm to replace the need for textual descriptions in the classification process.
Correct Answer: B 🗳️
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During the process of data cleansing, which of the following steps is NOT typically performed?
- A. Removing duplicates
- B. Identifying and handling missing values
- C. Collecting additional data
- D. Transforming data into a different format
Correct Answer: C 🗳️
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In the transformer architecture, what is the purpose of positional encoding?
- A. To encode the semantic meaning of each token in the input sequence.
- B. To encode the importance of each token in the input sequence.
- C. To remove redundant information from the input sequence.
- D. To add information about the order of each token in the input sequence.
Correct Answer: D 🗳️
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Hyperparameter tuning is used for what purpose in machine learning experimentation?
- A. Adjusting the weights and biases of a neural network to optimize its performance.
- B. Selecting the best ML algorithm for a given task.
- C. Collecting and preprocessing data to improve the accuracy of the model.
- D. Selecting the optimal values for non-trainable parameters, such as learning rate or batch size.
Correct Answer: D 🗳️
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What is the role of CLIP (Contrastive Language-Image Pretraining) in text-to-image generation?
- A. CLIP provides a common embedding space for both the textual and image modalities.
- B. CLIP is used to enhance datasets through data augmentation for text-to-image generation.
- C. CLIP is used to generate image captions from textual input.
- D. CLIP is used to convert textual input into image embeddings.
Correct Answer: A 🗳️
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