Security, Compliance and Governance for AI Solutions

AI systems need more than strong technical performance.

They also need clear controls around security, privacy, fairness, transparency, and accountability. On this course, you’ll explore the principles and AWS practices that help organisations use artificial intelligence responsibly and with greater confidence.

You’ll examine how security, compliance, and governance fit across the AI lifecycle, from the data used to train models through to deployment and ongoing monitoring.

Protect data and AI systems

Explore the security considerations involved in AI and machine learning solutions, including data privacy, access controls, and the protection of sensitive information.

You’ll consider how AWS tools and security practices can help reduce risk across AI workloads.

Navigate responsible and explainable AI

Examine fairness, bias, transparency, explainability, and human-centred design. You’ll consider why these principles matter when AI influences decisions and how responsible AI practices can support more trustworthy outcomes.

Apply compliance and governance principles

Explore how governance frameworks, policies, monitoring, and oversight help organisations manage AI responsibly.

You’ll consider how compliance requirements can influence the way models and AI-powered services are designed, deployed, and maintained.

By the end, you’ll have a stronger understanding of the controls and practices that support secure, compliant, and responsible AI solutions on AWS, preparing you to consolidate your learning through AWS AI Practitioner exam preparation.