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Data privacy in AI refers to protecting personal and sensitive information used to train, operate, or interact with AI systems. It encompasses how data is collected, stored, processed, and shared, and whether individuals have control over their own information.
With AI systems processing vast amounts of personal data, privacy breaches can erode trust and lead to significant legal penalties under regulations like GDPR.
Apple processes Siri voice requests on-device where possible, rather than sending audio to cloud servers, to protect user privacy.
AI Governance
AI governance is the set of policies, regulations, and frameworks that guide the ethical development and deployment of AI systems. It covers everything from data handling practices to accountability structures and compliance requirements.
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.
Training Data
Training data is the collection of examples used to teach a machine learning model. The model analyses this data to discover patterns and relationships, which it then uses to make predictions or generate outputs on new, unseen data.
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.