Introduction

The course has three sections, each ending with a knowledge check:

1. What responsible AI is: its definition, the challenges it addresses, and its core dimensions.
2. Building responsible AI systems: AWS services and tools, responsible model selection, and responsible dataset preparation.
3. Transparent and explainable models: what transparency and explainability mean, safety versus transparency trade-offs, and human-centered design for explainable AI.