Try and practice the latest NVIDIA : NCA-GENM real questions & answers
Updated: Jul 18, 2026
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NVIDIA NCA-GENM Exam Overview:
| Certification Vendor: | NVIDIA |
| Exam Name: | NVIDIA Certified Associate - Generative AI Multimodal |
| Exam Number: | NCA-GENM |
| Passing Score: | Not publicly disclosed |
| Available Languages: | English |
| Exam Format: | Multiple-choice |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | 2 years |
| Real Exam Qty: | 50-60 |
| Exam Price: | $125 USD |
| Related Certifications: | NVIDIA Certified Associate - Generative AI LLMs (NCA-GENL) NVIDIA Certified Associate - AI Infrastructure and Operations (NCA-AIIO) |
| 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 |
|---|---|---|
| Performance Optimization | 10% | - Monitoring and improving system efficiency - Techniques for optimizing AI performance |
| Multimodal Data | 15% | - Handling and integrating text, image, and audio data - Applications and use cases |
| Experimentation | 25% | - Model evaluation and comparison - Hypothesis testing - A/B testing - Experimental design |
| Trustworthy AI | 5% | - Ensuring fairness and transparency - Ethical considerations in AI development |
| Data Analysis & Visualization | 10% | - Data preprocessing and feature engineering - Visualization techniques for multimodal data |
| Core ML & AI Knowledge | 20% | - Basic concepts and terminology - Key algorithms and techniques |
| Software Development & Engineering | 15% | - Integration and deployment of multimodal AI systems - Python libraries for multimodal AI |
NVIDIA Generative AI Multimodal Sample Questions:
1. In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?
A) Support vector machine (SVM)
B) Decision tree
C) K-means clustering
D) Generative adversarial network (GAN)
2. What is the significance of using a U-Net like architecture in denoising diffusion probabilistic models?
A) To classify input images as noisy or clean.
B) To generate new images from pure noise.
C) To segment noisy patches in input images.
D) To detect noisy objects in input images.
3. What advantage does multimodal learning have over unimodal learning?
A) It is easier to collect multimodal data than unimodal data.
B) It requires fewer data samples for learning.
C) It is more reliable than unimodal learning.
D) It can capture more complex patterns and relationships in data.
4. In the development of Trustworthy AI, what is the significance of 'Certification' as a principle?
A) It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
B) It ensures that AI systems are transparent in their decision-making processes.
C) It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
D) It requires AI systems to be developed with an ethical consideration for societal impacts.
5. In multimodal machine learning, what does 'early fusion' refer to?
A) Ignoring certain modalities and only using one modality for analysis and prediction.
B) Training separate models for each modality and then combining their predictions.
C) Integrating different modalities at the beginning of the model pipeline.
D) Implementing the model in the early stages of development of the ML solution.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: C |
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