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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Core AI and Machine Learning Fundamentals | - Machine learning basics
|
| Topic 2: NVIDIA AI Ecosystem | - NVIDIA tools and frameworks
|
| Topic 3: Responsible and Trustworthy AI | - Ethical AI principles - Bias and safety considerations |
| Topic 4: Generative AI Concepts | - Generative models
|
| Topic 5: Multimodal AI Systems | - Multimodal model design - Cross-modal learning
|
NVIDIA Generative AI Multimodal Sample Questions:
In large-language models, what is the purpose of the attention mechanism?
- A. To measure the importance of the words in the output sequence.
- B. To capture the order of the words in the input sequence.
- C. To determine the order in which words are generated.
- D. To assign weights to each word in the input sequence.
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What is the correct order of steps in an ML project?
- A. Model evaluation, Data collection, Data preprocessing, Model training
- B. Data collection, Data preprocessing, Model training, Model evaluation
- C. Model evaluation, Data preprocessing, Model training, Data collection
- D. Data preprocessing, Data collection, Model training, Model evaluation
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Which visualization technique is suitable for representing the distribution of performance scores for different multimodal ML models over different modalities?
- A. Heatmap
- B. Histogram
- C. Pie chart
- D. Box plot
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You have been given a dataset with missing values. What is the first step you should take with the data?
- A. Remove the columns with missing values.
- B. Analyze the patterns and distribution of missing values.
- C. Remove the rows with missing values.
- D. Fill in the missing values with a default value.
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What is contrastive learning in the context of multimodal deep learning? Pick the 2 correct responses below.
- A. Contrastive learning is a technique used to manipulate and analyze multimodal data using Generative AI.
- B. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the different objects and decreases the similarity of representations across modalities for same objects.
- C. In a multimodal context, usually, contrastive learning decreases the similarity of representations across modalities for the same objects and increases the similarity of representations across modalities for different objects.
- D. Contrastive learning is a technique used to train deep learning models by comparing similar and dissimilar inputs and optimizing the model to maximize the similarity between representations of similar inputs and minimize the similarity between representations of dissimilar inputs.
- E. In a multimodal context, usually, contrastive learning increases the similarity of representations across modalities for the same objects and decreases the similarity of representations across modalities for different objects.
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