RAPIDS Workshop

GPU computing is revolutionising data science with RAPIDS, a powerful new suite of open source software for executing end-to-end data science training pipelines. It’s all done completely in the GPU, reducing training time from hours to minutes. The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes. RAPIDS is an open source data analytics and machine learning acceleration platform and fully supported by NVIDIA

Ideal for Data Engineers, Data Scientists and Data Science Managers, XENON’s  training course enables you to learn how to perform multiple analysis tasks on large datasets using RAPIDS.


  • Basic machine learning concepts: classification, clustering
  • Python, Pandas, Scikit-learn
  • Basic concept of data sciences and work flow
  • Familiar with Jupyter Notebook environment


  • RAPIDS Technical Overview and Software Architecture
  • RAPIDS Use Cases and Implementation Scenarios
  • Hand-on Session Covering Data ETL Pipeline and Algorithm Demonstration

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