Detailed Syllabus

Lower
Secondary

Grades 7–8 90 minutes · 100 marks

Hands-on mechanics by hand and in simple Python: n-gram language models, tokenisation, a single neuron, the ML pipeline, and AI agents.

// who it's for

Students, teachers and coaches preparing for the first band with explicit model mechanics, coding-related reasoning, and practical AI problem framing.

// what success looks like

Learners explain how simple language models and ML pipelines work, analyse bias and failure points, and reason with short Python-based tasks.

// where this band sits

The four-band journey

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// focus of this band

Mechanics by hand and in simple Python - and the first explicit analysis of why outputs happen.

// learning outcomes

The five AI Pillars

Each Pillar leads with a disposition, then plain learning outcomes that combine what a learner knows and can do. The same five Pillars return in every band, a little deeper each time.

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Learning outcomes
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Assessment format
90 min
20 MCQ [40] + 3 structured / practical tasks [60]
Total 100 marks
Emerging-tech theme task each year · Python 3 + Jupyter / Colab
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Hands-on Practice Lab
Play the Lower Secondary Practice Lab
Explore embeddings, predictions and verification through hands-on activities, then build a classifier of your own.
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// ready to practise
Try the Lower Secondary problem sets
Three interactive sets: by-hand modelling, short Python reasoning, and clear marking guides.
🐍 Python Notebook · run real code in your browser Build a tiny AI, end to end: tokens to agents in 8 runnable steps Open →
Overview Next band → Upper Secondary