Recognise AI approaches
Distinguish search, knowledge-based, machine-learning and generative systems.
Intelligent systems
Artificial intelligence: concepts and responsible applications
Understand how AI systems represent problems, learn from data and generate outputs—and how to evaluate their limitations.
View curriculumproblem → representation
representation → algorithm
algorithm → output
evaluate(accuracy, bias,
transparency, impact)
representation → algorithm
algorithm → output
evaluate(accuracy, bias,
transparency, impact)
Learning outcomes
Understand AI beyond the headline.
Evaluate outputs
Assess accuracy, evidence, robustness and appropriateness for a defined context.
Consider consequences
Analyse privacy, bias, accountability, transparency and human oversight.
Curriculum
Four foundations of AI
The course combines conceptual lessons, practical examples and responsible-use case studies.
- Intelligence, automation and augmentation
- Symbolic and data-driven approaches
- Capabilities versus marketing claims
- State spaces and search strategies
- Rules, knowledge graphs and reasoning
- Uncertainty and probabilistic decisions
- Machine learning foundations
- Language models and generative AI
- Hallucination, grounding and verification
- Privacy, security and data rights
- Bias, fairness and accessibility
- Accountability and impact assessment