NVIDIA NCA-GENM Questions & Answers - in .pdf
- Total Q&A: 58
- Update: Aug 29, 2026
- Price: $59.99
- Vendor: NVIDIA
- Exam Code: NCA-GENM
- Exam Name: NVIDIA Generative AI Multimodal
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- Total Q&A: 58
- Update: Aug 29, 2026
- Price: $59.99
- Vendor: NVIDIA
- Exam Code: NCA-GENM
- Exam Name: NVIDIA Generative AI Multimodal
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NVIDIA NCA-GENM Exam Overview:
| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA Certified Associate - Generative AI Multimodal |
| Exam Number: | NCA-GENM |
| Exam Price: | $125 USD |
| Exam Duration: | 60 minutes |
| Related Certifications: | NVIDIA Certified Associate - Generative AI LLMs (NCA-GENL) NVIDIA Certified Associate - AI Infrastructure and Operations (NCA-AIIO) |
| Real Exam Qty: | 50-60 |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple-choice |
| Passing Score: | Not publicly disclosed |
| Available Languages: | English |
| Sample Questions: | NVIDIA NCA-GENM Sample Questions |
| Exam Way: | Online, remotely proctored |
| Pre Condition: | A basic understanding of generative AI and multimodal models. |
| Official Syllabus URL: | https://www.nvidia.com/en-us/learn/certification/generative-ai-multimodal/ |
NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Performance Optimization | 10% | - Monitoring and improving system efficiency - Techniques for optimizing AI performance |
| Topic 2: Data Analysis & Visualization | 10% | - Visualization techniques for multimodal data - Data preprocessing and feature engineering |
| Topic 3: Core ML & AI Knowledge | 20% | - Basic concepts and terminology - Key algorithms and techniques |
| Topic 4: Software Development & Engineering | 15% | - Python libraries for multimodal AI - Integration and deployment of multimodal AI systems |
| Topic 5: Experimentation | 25% | - Model evaluation and comparison - Experimental design - Hypothesis testing - A/B testing |
| Topic 6: Multimodal Data | 15% | - Applications and use cases - Handling and integrating text, image, and audio data |
| Topic 7: Trustworthy AI | 5% | - Ensuring fairness and transparency - Ethical considerations in AI development |
NVIDIA Generative AI Multimodal Sample Questions:
Question 1
In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?
A. Generative adversarial network (GAN)
B. Support vector machine (SVM)
C. Decision tree
D. K-means clustering
Question 2
In the development of Trustworthy AI, what is the significance of 'Certification' as a principle?
A. It ensures that AI systems are transparent in their decision-making processes.
B. It requires AI systems to be developed with an ethical consideration for societal impacts.
C. It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
D. It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
Question 3
Which technique involves leveraging pre-trained models to achieve efficient results with less data and computation?
A. Prompt engineering
B. Neural network integration
C. Transfer learning
D. State management and composition
Question 4
What is the role of CLIP (Contrastive Language-Image Pretraining) in text-to-image generation?
A. CLIP is used to enhance datasets through data augmentation for text-to-image generation.
B. CLIP provides a common embedding space for both the textual and image modalities.
C. CLIP is used to generate image captions from textual input.
D. CLIP is used to convert textual input into image embeddings.
Question 5
Which framework is used for conversational AI models development?
A. NVIDIA DeepStream
B. NVIDIA Clara
C. NVIDIA Metropolis
D. NVIDIA NeMo
Solutions:
| Question 1 Answer: A | Question 2 Answer: D | Question 3 Answer: C | Question 4 Answer: B | Question 5 Answer: D |
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