Investigate · Ages 13–17
AI & Data Lab
Explore how AI learns from examples, why data quality matters and where human judgement belongs.
Proposed pathway. This is a curriculum direction for future delivery. Dates, session length, fees, equipment and venue are to be confirmed. Submit a programme request to express interest and discuss feasibility.
A project with a purpose
Design a small classification experiment, test new examples and explain its limitations.
Illustrative project direction; the final brief will be adapted to the group.
Learning goals
- Distinguish a programmed rule from a learned pattern.
- Separate training examples from test examples.
- Discuss bias, privacy and responsible use with concrete examples.
Suggested learning journey
STEP 1
Question
Choose a classroom-scale question a model could investigate.
STEP 2
Prepare examples
Organise a small dataset without personal or sensitive information.
STEP 3
Evaluate
Try unseen examples and record errors.
STEP 4
Explain
Present what the model can do, where it fails and when a person should decide.
Equipment & preparation
Suggested tools: a browser-based learning environment, small non-personal datasets and optional introductory Python.
Where could this lead?
A more independent data project or an interdisciplinary innovation challenge.
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