Duration

1 days.

Prerequisites

  • Familiarity with basic concepts of machine learning
  • Familiarity with basic concepts of generative AI on Google Cloud in Vertex AI

Skills Gained

  • Overview of Responsible AI principles and practices
  • Implement processes to check for unfair biases within machine learning models
  • Explore techniques to interpret the behavior of machine learning models in a human-understandable manner
  • Create processes that enforce the privacy of sensitive data in machine learning applications
  • Understand techniques to ensure safety for generative AI-powered applications

Who Can Benefit?

Machine learning practitioners and AI application developers wanting to leverage generative AI in a responsible manner.

    Outline for Introduction to Responsible AI in Practice Training

    Course Outline

    AI Principles and Responsible AI

    • Google's AI Principles
    • Responsible AI practices
    • General best practices

    Fairness in AI

    • Overview of Fairness in AI
    • Examples of tools to study fairness of datasets and models
    • Lab: Using TensorFlow Data Validation and TensorFlow Model Analysis to Ensure Fairness

    Interpretability of AI

    • Overview of Interpretability in AI
    • Metric selection
    • Taxonomy of explainability in ML Models
    • Examples of tools to study interpretability
    • Lab: Learning Interpretability Tool for Text Summarization

    Privacy in ML

    • Overview of Privacy in ML
    • Data security
    • Model security
    • Security for Generative AI on Google Cloud

    AI Safety

    • Overview of AI Safety
    • Adversarial testing
    • Safety in Gen AI Studio
    • Lab: Responsible AI with Gen AI Studio
    05/29/2024 - 05/29/2024
    09:00 AM - 05:00 PM
    Eastern Standard Time
    Online Virtual Class
    USD $900.00
    Enroll