A comprehensive exploration of AI concepts - understand how machine learning, training data, bias, and ethics really work.
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Discover the two ways to make a computer smart — human-written RULES versus LEARNING FROM EXAMPLES — and build your own rule-based classifier in Python
Discover what a dataset really is — a table of examples with features and labels — and build your own tiny labelled dataset in Python as a list of dicts
Get full access to all 8 lessons in Year 2 Term 5: AI Concepts Deep Dive.
Book a Class →Write a real spam-detector classifier in Python using keyword rules and if/elif — then discover exactly where hand-written rules break, and why machines need to learn instead
Peek inside chatbots and Large Language Models — build your own keyword-matching chatbot in Python, then discover the 'super-powered autocomplete' idea behind ChatGPT and why it can be confidently wrong
Discover why AI can be unfair to some groups, learn that AI reflects its training data, and become a Bias Detective — test a rule-based classifier for unfairness and fix it
Learn to spot deepfakes and AI-made misinformation, protect your privacy, and be a responsible AI citizen — then plan your end-of-term AI Investigation Report
Turn your Week 6 investigation into a real Python project — a program that PRINTS a clear, sectioned report on one real AI system, plus a mini rule-based classifier demo that proves a point from your report
Term 5 finale — present your AI Investigation at the class AI Summit, debate a big AI question, ace a quiz on AI concepts, and earn your AI Scholar Badge