Loading
Loading
Red teaming is a structured process of stress-testing AI systems with adversarial prompts and scenarios to uncover safety, security, and reliability failures.
It identifies vulnerabilities before deployment, reducing harm and improving trust in high-impact AI products.
Before launch, a fintech company runs red-team exercises to test if its assistant can be manipulated into disclosing sensitive data.
AI Safety
AI safety is a research field focused on ensuring that AI systems behave as intended and do not cause unintended harm. It encompasses technical challenges like robustness and reliability, as well as broader concerns about long-term risks from increasingly capable systems.
Responsible AI
Responsible AI is an approach to developing and deploying AI systems that prioritises fairness, transparency, accountability, and societal benefit. It encompasses practices and principles designed to minimise harm and ensure AI serves people equitably.
Guardrails
Guardrails are safety and quality controls around AI systems that restrict harmful, non-compliant, or low-quality outputs. They can include policy filters, schema validation, and response checks before results reach users.
Our programme follows a structured Level 4 curriculum with project-based learning, practical workflows, and guided implementation across business and career use cases. Funded route available for UK citizens and ILR holders.