ICT · Pioneers 11–15 · Year 9–10
Data science, AI and cybersecurity
Should an algorithm decide who gets a loan?
What you will learn
- Clean and analyse a data set with Python (pandas or spreadsheets) and visualise it
- Train a simple classifier and evaluate accuracy and bias
- Explain common cyber threats and defences: encryption, 2FA, social engineering
- Debate ethical use of AI with evidence and propose a policy
Helpful to know first: Python functions; Averages and charts
Discover
Think first: Should an algorithm decide who gets a loan? Say or jot one idea before you read on.
Learn — core route
- Clean a messy CSV
- Teachable-machine style classifier
- Cyber attack case studies
- AI policy debate
Lessons in this subject: Learn Topics · ICT
Practise — check a common mix-up
An accurate model is a fair model.
Encryption makes data safe forever.
Apply / Create — Responsible AI Report
Analyse a data set, build and evaluate a classifier for bias, and write a 500-word report recommending safeguards, with charts.
Evidence type: code · accessible alternative always allowed (speak it, draw it, or show an adult).
How it is judged (rubric)
- Beginning: Loads data
- Developing: Model built
- Secure: Model evaluated for bias; report with safeguards
- Extending: Quantifies fairness metrics and trade-offs
Explain — say what you did
Review later
We'll offer a quick memory check in 7, 21 and 45 days. Mark this done and your Today page will remind you gently.
For grown-ups · framework mappings
- aligned to UK NC (Computing) · KS4 Computing: data; ethics; security
- aligned to CSTA-aligned · 3A-DA-11, 3A-IC-24, 3A-NI-05
Status: Live · reviewed
What's next?