Fundamentals of Accelerated Data Science NVFADS-QA

NVFADS-QA
Price on request

Data science is about using scientific methods, processes, algorithms, and systems to analyse and extract insight from data. We believe organisations that master AI, Cloud, and Data can turn information into a competitive advantage. This hands-on workshop demonstrates how GPU-accelerated tools can transform data science workflows, enabling faster experimentation, greater scalability, and more cost-effective outcomes.Across the workshop, learners use RAPIDS libraries to accelerate data manipulation, machine learning, and graph analytics. Participants work with cuDF, cuML, cuGraph, and related tools to process large and larger-than-memory datasets. The course culminates in a population-scale project that applies GPU-accelerated analytics to simulate and respond to an epidemic affecting the UK, reinforcing practical, real-world application of skills.

Use cuDF to accelerate pandas, Polars, and Dask workflows for analysing datasets of varying sizes
Ingest and prepare large and larger-than-memory datasets directly on single or multiple GPUs
Apply GPU-accelerated supervised and unsupervised machine learning algorithms using cuML
Use algorithms such as XGBoost to address a range of data science problems
Create and analyse complex network data using NetworkX and cuGraph
Deploy machine learning models to an NVIDIA Triton Inference Server for optimised performance
Integrate multiple large datasets to perform iterative, real-world analysis tasks

Fundamentals of Accelerated Data Science

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