Skip to main content

Fundamentals of Accelerated Data Science with RAPIDS

When

9 a.m. – 4:20 p.m., Oct. 1, 2026

Where

Main Library room B201

In this Deep Learning Institute (DLI) workshop, participants will learn how to build and execute end-to-end GPU-accelerated data science workflows that enable them to quickly explore, iterate, and make predictions. Using the RAPIDS accelerated data science libraries, participants will apply a wide variety of GPU-accelerated machine learning algorithms, including XGBoost, cuGRAPH’s single-source shortest path, and cuML’s KNN, DBSCAN, and logistic regression to perform data analysis at scale.

By participating in this workshop, you’ll:

  • Implement GPU-accelerated data preparation and feature extraction using cuDF and
    Apache Arrow data frames
  • Apply a broad spectrum of GPU-accelerated machine learning tasks using XGBoost and
    a variety of cuML algorithms
  • Execute GPU-accelerated graph analysis with cuGraph, achieving massive-scale
    analytics in small amounts of time
  •  Rapidly achieve massive-scale graph analytics using cuGraph routines


Topics: RAPIDS, cuDF, XGBoost, cuML, cuGraph, Dask, cuPy, pandas, NumPy, Bokeh,data
science, data analytics, machine learning
Prerequisites: Experience with Python, ideally including pandas and NumPy.
Assessment Type: Code-based
Certificate Available


Register here