Skip to main content Accessibility help
×
  1. Home
  2. Search

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

1 results

  • 6 - Cloud Computing

  • from Part II - Tools for Data Science
  • Chirag Shah, University of Washington
  • Book:
    A Hands-On Introduction to Data Science with Python
    Published online:
    07 February 2026
    Print publication:
    22 January 2026, pp 151-180

  • Summary

    This chapter introduces cloud computing platforms essential for modern data science work. It covers three major cloud services: Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS). Students learn to create virtual machines, configure storage, and access cloud resources through SSH connections. The chapter demonstrates hands-on Python development using browser-based IDEs like Google Colab, Azure Machine Learning notebooks, and AWS Cloud9. Key topics include setting up accounts, managing costs through free tiers, and leveraging cloud resources for data science projects. The chapter also covers Hadoop for big data processing and discusses platform migration strategies. Practical exercises guide students through currency conversion programs, interactive calculations, and Olympic year predictions, emphasizing that cloud computing skills are now essential for data science professionals due to scalable processing power and storage capabilities.