Fundamentals of Accelerated Data Science (FADS)

 

Course Overview

Learn how to perform multiple analysis tasks on large datasets using NVIDIA RAPIDS™, a collection of data science libraries that allows end-to-end GPU acceleration for data science workflows.

Certifications

Prerequisites

Experience with Python, ideally including pandas and NumPy.

Suggested resources to satisfy prerequisites: Kaggle's pandas Tutorials, Kaggle's Intro to Machine Learning, Accelerating Data Science Workflows with RAPIDS

Course Objectives

  • 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

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Prices & Delivery methods

Online Training

Duration
1 day

Price
  • on request
Classroom Training

Duration
1 day

Price
  • on request

Click on town name or "Online Training" to book Schedule

Instructor-led Online Training:   This is an Instructor-Led Online (ILO) course. These sessions are conducted via WebEx in a VoIP environment and require an Internet Connection and headset with microphone connected to your computer or laptop. If you have any questions about our online courses, feel free to contact us via phone or Email anytime.

United States

Online Training 07:30 Pacific Daylight Time (PDT) This course is being delivered by a partner Enroll