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How to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results.

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Course

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  1. Description
  2. Information
  3. Certificate

Description

Data science is about using scientific methods, processes, algorithms, and systems to analyze and extract insights from data. It empowers organizations to turn data into a valuable resource, leading to smarter decision-making, improved operations, and enhanced customer experiences. In this workshop, you will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results.

Information

Upon completion, you will be able to perform various data science tasks more efficiently, enabling more iteration cycles and drastically improving productivity:

  • Use cuDF to accelerate pandas, Polars, and Dask for analyzing datasets of all sizes efficiently.
  • Utilize a wide variety of machine learning algorithms, including XGBoost, for different data science problems.
  • Deploy machine learning models on a Triton Inference Server to deliver optimal performance.
  • Learn and apply powerful graph algorithms to analyze complex networks with NetworkX and cuGraph.
  • Perform multiple analysis tasks on massive datasets to stave off a simulated epidemic outbreak effecting the UK.

More detailed information and links for the course can be found on the course website.

Certificate

The certificate for the course can be found below:

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How to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results.

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