Introduction to Responsible AI in Practice Training

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

Students will learn,

• 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

Module 1: AI Principles and Responsible AI

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

Module 2: Fairness in AI

• Overview of Fairness in AI
• Examples of tools to study fairness of datasets and models

Module 3: Interpretability of AI

• Overview of Interpretability in AI
• Metric selection
• Taxonomy of explainability in ML Models
• Examples of tools to study interpretability

Module 4: Privacy in ML

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

Module 5: AI Safety

• Overview of AI Safety
• Adversarial testing
• Safety in Gen AI Studio