Trustworthy AI Design

Course Description

Equip your team with the essentials to design and deploy AI that people can trust—explainable, private, secure, and inclusive. This micro-course turns high-level principles into practical steps and checklists your staff can apply immediately across the AI lifecycle. The result: lower risk, stronger compliance, and AI outcomes that stakeholders can understand and support.

Who Should Take This Course

Ideal for cross-functional teams: product managers, business analysts, data scientists, developers, consultants, UX researchers, compliance and risk officers, and line-of-business leaders. Suits organisations beginning AI adoption as well as teams seeking to harden existing AI use cases.

Prerequisites

No prior experience needed.

What You Will Learn

• Explain model behaviour in plain language using approachable interpretability techniques and produce stakeholder-ready rationales.
• Apply privacy-preserving approaches (anonymisation basics, differential privacy concepts, federated learning patterns) to protect sensitive data.
• Implement secure AI development practices, including threat modelling for ML systems, pipeline hardening, and safe prompt/API handling.
• Design inclusive, participatory workflows that surface bias, incorporate diverse user input, and improve accessibility.
• Create lightweight governance artefacts—risk assessments, model cards, and decision logs—that align with organisational and regulatory expectations.
• Identify red flags in current AI initiatives and draft an action plan to improve trustworthiness end to end.