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NVIDIA NCA-GENM Exam Syllabus Topics:

SectionObjectives
Multimodal AI Systems- Cross-modal learning
  • 1. Text-image integration
    • 2. Audio-visual understanding
      - Multimodal model design
      Generative AI Concepts- Generative models
      • 1. Diffusion models
        • 2. Transformers and LLM basics
          Responsible and Trustworthy AI- Bias and safety considerations
          - Ethical AI principles
          Core AI and Machine Learning Fundamentals- Machine learning basics
          • 1. Supervised and unsupervised learning
            • 2. Neural networks fundamentals
              NVIDIA AI Ecosystem- NVIDIA tools and frameworks
              • 1. NeMo framework usage
                • 2. GPU-accelerated AI workflows

                  NVIDIA Generative AI Multimodal Sample Questions:

                  Question #1

                  During the process of data cleansing, which of the following steps is NOT typically performed?

                  • A. Transforming data into a different format
                  • B. Identifying and handling missing values
                  • C. Removing duplicates
                  • D. Collecting additional data
                  Reveal Solution  Discussion  0

                  Correct Answer: D  🗳️

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                  Question #2

                  You have been given a dataset with missing values. What is the first step you should take with the data?

                  • A. Analyze the patterns and distribution of missing values.
                  • B. Fill in the missing values with a default value.
                  • C. Remove the rows with missing values.
                  • D. Remove the columns with missing values.
                  Reveal Solution  Discussion  0

                  Correct Answer: A  🗳️

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                  Question #3

                  How does the batch size influence VRAM consumption during inference with ML models on GPUs?

                  • A. Increasing or decreasing the batch size has the same impact on VRAM consumption.
                  • B. Increasing the batch size reduces VRAM consumption because more data can be processed in parallel.
                  • C. The batch size has no impact on VRAM consumption during inference.
                  • D. Decreasing the batch size reduces VRAM consumption.
                  Reveal Solution  Discussion  0

                  Correct Answer: D  🗳️

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                  Question #4

                  What is the significance of using a U-Net like architecture in denoising diffusion probabilistic models?

                  • A. To detect noisy objects in input images.
                  • B. To segment noisy patches in input images.
                  • C. To classify input images as noisy or clean.
                  • D. To generate new images from pure noise.
                  Reveal Solution  Discussion  0

                  Correct Answer: D  🗳️

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                  Question #5

                  In the development of Trustworthy AI, what is the significance of 'Certification' as a principle?

                  • A. It involves verifying that AI models are fit for their intended purpose according to regional or industry- specific standards.
                  • B. It requires AI systems to be developed with an ethical consideration for societal impacts.
                  • C. It ensures that AI systems are transparent in their decision-making processes.
                  • D. It mandates that AI models comply with relevant laws and regulations specific to their deployment region and industry.
                  Reveal Solution  Discussion  0

                  Correct Answer: A  🗳️

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