Lesson 1 · AI Around Us
The many shapes of data: numbers, words, images, audio, video and sensors.
A friend asks, "Which sport should I try?" Before you answer, your brain quietly gathers clues: their age, do they like indoor or outdoor, how much free time they have, do they enjoy teams or going solo.
All of those clues are data — and data is the fuel every AI runs on.
Data isn't just numbers. It can be:
No data, no learning. An AI with no examples is like a student with no textbook.
Say we want an AI to recommend movies. We'd collect a little table:
| Friend | Age | Likes action? | Watch time |
|---|---|---|---|
| Aarav | 13 | Yes | Evenings |
| Meera | 12 | No | Weekends |
| Kabir | 14 | Yes | Late night |
Each row is an example; each column is a piece of data the AI can learn from.
Which of these is an example of image data?
Make a small movie-recommendation dataset: invent 5 people, give each 3 features (like age, likes-comedy?, free time), and their favourite movie. You've just prepared data the way an AI team does.
The better and more useful your data, the better the AI's suggestions. Data first, magic later.
To recommend a sport (not a movie), which single piece of data do you think would help the most? Why that one?
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