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Machine Learning: A Beginner’s Guide

Class Code


Class Description


Learn about Machine Learning patterns and use cases in the real world, while getting a review of statistics and data analytics to be more data-minded, and helping to understand the Data Science process.

After this course, you will be able to:

  • Describe the role of Machine Learning and where it fits into Information Technology strategies
  • Explain the technical and business drivers that result from using Machine Learning
  • Describe Supervised and Unsupervised learning techniques and usages
  • Understand techniques like Classification, Clustering, and Regression
  • Discuss how to identify which kinds of technique to be applied for a specific use case

Topic Outline:

  • Course Introduction
  • History and background of Machine Learning
  • Compare Traditional Programming Vs Machine Leaning 
  • Supervised and Unsupervised Learning Overview
  • Machine Learning patterns
    - Classification
    - Clustering
    - Regression
  • Gartner Hype Cycle for Emerging Technologies
  • Machine Learning offerings in Industry
  • Hands-on exercise: Apply the Machine Learning Basics to real-life use case
  • References and Next steps

University IT Technology Training classes are only available to Stanford University staff, faculty, or students. A valid SUNet ID is needed in order to enroll in a class.