Free PDF Quiz NCP-ADS - Perfect NVIDIA-Certified-Professional Accelerated Data Science Valid Mock Exam

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NVIDIA NCP-ADS Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Analysis14%- Data visualization and graph analytics
- Time-series analysis and anomaly detection
- Distributed and parallel data processing
- Exploratory Data Analysis (EDA)
Topic 2: MLOps19%- Model deployment and serving
- Monitoring, logging and maintenance
- Pipeline automation and orchestration
- End-to-end workflow management
Topic 3: GPU and Cloud Computing16%- GPU architecture and acceleration principles
- Resource management and scaling strategies
- Cloud GPU environments and deployment
- CRISP-DM and data science methodology
Topic 4: Data Manipulation and Software Literacy19%- Dependency management and containerization
- Performance profiling and optimization tools
- Data processing libraries selection and usage
- GPU-accelerated ETL workflows
Topic 5: Machine Learning15%- Distributed training strategies
- Model training and hyperparameter tuning
- Model evaluation and validation
- GPU-accelerated ML frameworks and algorithms
Topic 6: Data Preparation17%- Feature engineering and data type optimization
- Data cleaning, preprocessing and transformation
- Workflow monitoring and bottleneck identification
- Data validation and quality assurance

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NVIDIA-Certified-Professional Accelerated Data Science Sample Questions (Q140-Q145):

NEW QUESTION # 140
In the CRISP-DM process, which NVIDIA technology is commonly used during the "Data Preparation" phase to handle large datasets efficiently?

Answer: A


NEW QUESTION # 141
You are working on a machine learning dataset with millions of rows and want to optimize performance on a GPU using CuDF. One of the features in your dataset represents categorical data with a limited number of unique values.
Which of the following data types should you use to maximize performance while reducing memory usage?

Answer: D


NEW QUESTION # 142
You are analyzing a transportation network where airports represent nodes and flight routes represent edges. You need to determine the most critical airports in the network based on how many shortest paths pass through them.
Which cuGraph centrality algorithm should you use for this task?

Answer: D


NEW QUESTION # 143
You are tasked with designing an ETL workflow for a large-scale data processing pipeline using NVIDIA technologies. You need to ensure that the extraction, transformation, and loading phases are optimized for performance using hardware acceleration.
Which of the following NVIDIA technologies would be most suitable for accelerating the ETL process?

Answer: A


NEW QUESTION # 144
You are processing a dataset of high-resolution images for deep learning training and want to optimize image loading, augmentation, and transformation on an NVIDIA GPU.
Which of the following statements correctly describes the role of NVIDIA DALI (Data Loading Library) in accelerating data preparation?

Answer: D


NEW QUESTION # 145
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