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Applied Artificial Intelligence and Machine Learning on Google Cloud Platform (GCP)

Class Code


Class Description

Effective immediately in response to COVID-19, all Technology Training classes will be delivered online until further notice.

In advance of each session, Tech Training will provide you with a Zoom link to your class, along with any required class materials.

This class will provide an overview of Machine Learning and Artificial Intelligence while exploring the advantages and capabilities of incorporating these technologies within the Google Cloud Platform (GCP) cloud computing services suite.

Google Cloud Platform (GCP) is a suite of cloud computing services offered by Google. This class will focus on using GCP to do Machine Learning and AI by providing an overview of these technologies. It will also cover the advantages of using a cloud service to perform ML and AI capabilities and allow learners to practice applying their new skillset with three Milestone projects.

Learning Objectives:

  • During this course, you will have the opportunity to:
  • Learn a basic understanding of TensorFlow
  • Review similarities and differences between Machine Learning and AI
  • Visually explore, clean, and prepare data
  • Use GCP for vision tasks (e.g., analyze photos and video)
  • Understand Natural Language Processing and sentiment analysis
  • Understand Text-to-Speech and Speech-to-Text conversion
  • Translate between thousands of available language pairs
  • Develop custom models using your data
  • Consider how to apply ML and AI using pre-trained models on common use cases with little or no coding


Topic Outline:

  • Course Introduction & Overview of Machine Learning and Artificial Intelligence


  • Milestone 1: Learn how to access GCP
    • Introduction to TensorFlow
    • Explore, analyze and clean data using GCP


  • Milestone 2: Explore Datalab and Dataprep for data analysis and preparation
    • Vision Intelligence
    • Image Analysis
    • Video Analysis
    • Text Intelligence
    • Natural Language Processing
    • Speech-to-Text, Text-to-Speech
    • Language Translation
    • Creating custom vs. pre-trained models


  • Milestone 3: Do photo analysis and text sentiment analysis
    • Next steps


Structured Activity/Exercises/Case Studies:

  • Milestone Project 1: Learn how to access GCP
  • Milestone Project 2: Explore Datalab and Dataprep for data preparation
  • Milestone Project 3: Use GCP to do photo analysis and text sentiment analysis



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