Introduction to Responsible AI in Practice

Name: Introduction to Responsible AI in Practice
Price: 1000.00 EUR

Explore Google's recommended best practices for responsible AI usage across different areas of focus.

1 day course

Supporting material

Private

A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

The development of AI has created new opportunities to improve the lives of people around the world, from business to healthcare to education. It’s also raised new questions about the best way to build fairness, interpretability, privacy, and safety into these systems.

In this course, you will do a high-level exploration of Google's recommended best practices for responsible AI usage across different areas of focus: Fairness, interpretability, privacy and safety. Along the way, you will learn how you can leverage different open-source tools and tools on Vertex AI to explore these concepts and spend time considering the different challenges that arise with generative AI.

This Introduction to Responsible AI in Practice course is available as a private training session that can be delivered via Virtual Classroom or at a location of your choice in Spain.

Course overview

Who should attend:

This course is perfect for machine learning practitioners and AI application developers wanting to leverage generative AI in a responsible manner.

What you'll learn:

By the end of this course, you will be able to:

Understand 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

Prerequisites

To get the most out of this course, participants should be familiar with the basic concepts of machine learning and generative AI on Google Cloud in Vertex AI.

Course agenda

Module 1: AI Principles & Responsible 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

Module 2: 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

Module 3: 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

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
Lab: Responsible AI with Gen AI Studio

Book this course

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