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NVIDIA Certified Professional - Accelerated Data Science (NCP-ADS)

Exam Overview

The NVIDIA Certified Professional - Accelerated Data Science certification validates expertise in using NVIDIA RAPIDS and GPU-accelerated tools for data science workflows including ETL, machine learning, graph analytics, and integration with Apache Spark on GPUs.

Exam Code: NCP-ADS Exam Duration: 120 minutes Number of Questions: 60-70 questions Exam Format: Multiple choice Cost: $200 USD Validity: 2 years Prerequisites: Recommended experience with data science, Python, and pandas/scikit-learn

Exam Domains

Domain 1: RAPIDS Framework Overview (15%)

  • RAPIDS ecosystem and components
  • GPU-accelerated data science benefits
  • RAPIDS installation and environment setup
  • Integration with the Python data science ecosystem

Domain 2: cuDF - GPU DataFrames (25%)

  • GPU-accelerated DataFrame operations
  • Data loading, transformation, and aggregation
  • pandas API compatibility and differences
  • Memory management and performance optimization

Domain 3: cuML - GPU Machine Learning (25%)

  • GPU-accelerated ML algorithms
  • Classification, regression, clustering, dimensionality reduction
  • Hyperparameter tuning on GPU
  • Model evaluation and cross-validation

Domain 4: cuGraph - GPU Graph Analytics (15%)

  • Graph construction and manipulation
  • Graph algorithms (PageRank, BFS, community detection)
  • Integration with cuDF for graph data
  • Scalable graph analytics patterns

Domain 5: GPU ETL and Spark Integration (20%)

  • GPU-accelerated ETL pipelines
  • RAPIDS Accelerator for Apache Spark
  • Dask-cuDF for multi-GPU and multi-node processing
  • Performance tuning for GPU data pipelines

Career Benefits

Job Opportunities

  • GPU Data Scientist
  • ML Engineer (GPU-accelerated)
  • Data Engineering Lead
  • AI/ML Platform Engineer
  • High-Performance Analytics Engineer