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NVIDIA NCA-GENM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Multimodal AI Systems | - Multimodal model design - Cross-modal learning
|
| NVIDIA AI Ecosystem | - NVIDIA tools and frameworks
|
| Core AI and Machine Learning Fundamentals | - Machine learning basics
|
| Responsible and Trustworthy AI | - Ethical AI principles - Bias and safety considerations |
| Generative AI Concepts | - Generative models
|
NVIDIA Generative AI Multimodal Sample Questions:
Which visualization technique is suitable for representing the distribution of performance scores for different multimodal ML models over different modalities?
- A. Histogram
- B. Pie chart
- C. Box plot
- D. Heatmap
Correct Answer: C 🗳️
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You are developing a ML model for image classification. You have a dataset with 10,000 images of cats, dogs and birds. Which of the following ML models would be the most appropriate choice for this task?
- A. Linear Regression
- B. K-Means Clustering
- C. Convolutional Neural Network (CNN)
- D. Logistic Regression
Correct Answer: C 🗳️
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In convolutional neural networks, we may use padding in both convolution and transposed convolution.
Which two (2) statements accurately describe padding in convolution and transposed convolution? Pick the 2 correct responses below.
- A. Padding in convolution enables convolution operations on the boundary pixels of the input. In transposed convolution, it removes rows and columns along the perimeter of the input after it is expanded with stride.
- B. Padding in convolution is used only when the input image is smaller than the filter size, while padding in transposed convolution is used only when the input image is larger than the filter size.
- C. Padding in convolution increases the spatial dimensions of the input feature map, while padding in transposed convolution decreases the spatial dimensions of the output feature maps.
- D. Padding in convolution and transposed convolution serve the same purpose of reducing the convolutional neural network's memory requirement and computational cost of the convolutional neural network.
- E. In a convolution operation, padding is added to the output after it has been expanded with the stride. On the other hand, in a transposed convolution operation, padding is added to the input before it is expanded with stride.
Correct Answer: A,C 🗳️
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What is the purpose of a kernel in a Convolutional Neural Network (CNN)?
- A. To perform convolution operations on input data.
- B. To normalize the input data.
- C. To classify the data into different categories.
- D. To calculate the loss function.
Correct Answer: A 🗳️
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In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?
- A. Decision tree
- B. Generative adversarial network (GAN)
- C. K-means clustering
- D. Support vector machine (SVM)
Correct Answer: B 🗳️
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