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NVIDIA NCA-GENM Exam Overview:
| Certification Vendor: | NVIDIA |
| Exam Name: | Generative AI Multimodal Certification Exam |
| Exam Number: | NCA-GENM |
| Exam Format: | Multiple choice |
| Exam Price: | $125 USD |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 60 minutes |
| Real Exam Qty: | 50-60 |
| Available Languages: | English, Chinese |
| Related Certifications: | NVIDIA-Certified Associate: Generative AI LLMs (NCA-GENL) |
| Passing Score: | Not publicly disclosed |
| Recommended Training: | Fundamentals of Generative AI Getting Started With Deep Learning |
| Exam Registration: | NVIDIA Certification Portal |
| Sample Questions: | NVIDIA NCA-GENM Sample Questions |
| Exam Way: | Online, remotely proctored |
| Pre Condition: | Basic understanding of generative AI concepts and principles |
| Official Syllabus URL: | https://www.nvidia.com/en-us/learn/certification/generative-ai-multimodal-associate/ |
NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Analysis and Visualization | 10% | - Interpretation of generative AI outputs - Analyzing multimodal datasets and outputs - Visualization techniques for model behavior and results |
| Topic 2: Software Development and Engineering | 15% | - Libraries, frameworks, and tools for multimodal AI - Best practices for building and maintaining systems - Development workflows for generative AI applications |
| Topic 3: Performance Optimization | 10% | - Model efficiency and inference optimization - Scalability and deployment considerations - Hardware acceleration with NVIDIA platforms |
| Topic 4: Multimodal Data | 15% | - Data preprocessing, fusion, and representation - Multimodal model architectures and integration - Characteristics of text, image, and audio data |
| Topic 5: Core Machine Learning and AI Knowledge | 20% | - Generative AI principles and techniques - Fundamental concepts of machine learning and deep learning - Neural network architectures relevant to multimodal systems |
| Topic 6: Trustworthy AI | 5% | - Reliability, fairness, and safety in generative systems - Robustness and error mitigation - Ethical considerations and responsible use |
| Topic 7: Experimentation | 25% | - Experiment design and methodology - Model training, fine-tuning, and evaluation - Metrics and validation strategies for generative models |
NVIDIA Generative AI Multimodal Sample Questions:
1. In LLM evaluation, what does "zero-shot learning" refer to?
A) The model's ability to perform tasks it has not been explicitly trained on
B) The model's ability to learn from zero examples
C) A technique to reduce training time to zero
D) The model's performance after extensive training
2. Which of the following is a component of the Content Authenticity Initiative?
A) Ethical AI development
B) Content credential
C) Data encryption
D) Content validity
3. Which metric is commonly used to evaluate machine-translation models?
A) Accuracy
B) Mean Absolute Error (MAE)
C) BLEU score
D) F1 score
4. What is the purpose of a kernel in a Convolutional Neural Network (CNN)?
A) To calculate the loss function.
B) To classify the data into different categories.
C) To perform convolution operations on input data.
D) To normalize the input data.
5. Which of the following best describes the role of machine learning in handling multimodal data?
A) To eliminate the need for human intervention in data analysis.
B) To enable models to learn from and interpret diverse data types.
C) To focus on textual data analysis.
D) To reduce the amount of data needed for accurate predictions.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: B |
By Ogden
