Responsible Artificial Intelligence Practices
AWS Skill Builder
Last updated March 9, 2026
Responsible Artificial Intelligence Practices is a free, hour-long course on building AI systems that people can trust. It starts by defining what "responsible AI" means and the core dimensions it covers, including the problem of bias in models and the particular risks generative AI introduces. From there it turns practical: responsible ways to choose a model and prepare datasets, and the difference between transparent and explainable models — including the trade-offs each demands and the principles of human-centered design that keep a person at the center of an AI decision. The course mixes text, interactive elements, illustrative graphics, and knowledge checks, and is conceptual throughout rather than a coding exercise.
What you'll learn
- What responsible AI means and its core dimensions
- How bias arises, and GenAI-specific risks
- Responsible model selection and dataset prep
- Transparent vs explainable models, and their trade-offs
- Human-centered design for explainable AI
- The AWS services/tools that support responsible AI
Frequently asked questions about Responsible Artificial Intelligence Practices
Who is Responsible Artificial Intelligence Practices for?
Anyone interested in AI and machine learning — independent of job role — who wants to understand responsible AI, from bias and fairness to transparency and explainability, at a conceptual level.
Is Responsible Artificial Intelligence Practices free?
Yes — Responsible Artificial Intelligence Practices is completely free to take.
What are the prerequisites for Responsible Artificial Intelligence Practices?
Foundational ML and AI knowledge and a prior AI use-cases course recommended first.
Why we suggest this course
For anyone who wants to understand fairness, bias, transparency, and explainability in AI well enough to ask the right questions — whether they build systems or simply rely on them. One thing to know: it is built by AWS, and one section maps these practices onto Amazon's own tools (Bedrock, SageMaker, Augmented AI), but the responsible-AI principles themselves are vendor-neutral.