Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 739 · 40 questions

AI tip (Accuracy = correct ÷ total × 100): Steps: 1 choose a problem → 2 collect examples → 3 label them → 4 check and correct bad labels (clean the data) → 5 split into training and test sets → 6 train → 7 test with new examples → 8 measure accuracy → 9 improve the data and retest. Accuracy = correct ÷ total × 100. Wrong = total − correct. Expected right = accuracy ÷ 100 × total. Keep some examples apart for testing (for example one fifth); the rest are for training.

1. 1.📋 Planning an AI project: which comes first — collect fruit photos or calculate percent right? (a) collect fruit photos (b) calculate percent right
2. 2.📋 Planning an AI project: which comes first — improve data, retest or test on new photos? (a) improve data, retest (b) test on new photos
3. 3.📋 Planning an AI project: which comes first — let it learn patterns or improve data, retest? (a) let it learn patterns (b) improve data, retest
4. 4.🎯 Kabir’s leaf identifier was tested on 4 new leaf photos and got 2 right. What is its accuracy in percent?
5. 5.📦 Tara collected 60 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
6. 6.🧪 What is accuracy? (a) correct ÷ total × 100 (b) total × 2 (c) correct + total (d) total − correct
7. 7.🧪 You can plan a simple AI project with… (a) only a big robot (b) nothing at all (c) paper and examples (d) a secret password
8. 8.📋 Planning an AI project: which comes first — calculate percent right or correct bad labels? (a) calculate percent right (b) correct bad labels
9. 9.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to see if it learned (c) to make it bigger (d) to make it faster
10. 10.❌ Meera’s leaf identifier was tested on 30 new leaf photos and got 24 right. How many did it get wrong?
11. 11.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) fewer examples (c) a louder speaker (d) a new colour screen
12. 12.📋 Planning an AI project: which comes first — calculate percent right or train the model? (a) calculate percent right (b) train the model
13. 13.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 29 right and Model B got 28 right. How many percentage points more accurate is Model A?
14. 14.🎯 Ishaan’s recycling sorter is 60% accurate. If it is tested on 50 new waste photos, how many should it get right?
15. 15.📋 Planning an AI project: which comes first — calculate percent right or collect fruit photos? (a) calculate percent right (b) collect fruit photos
16. 16.❌ Rohan’s handwriting reader was tested on 30 new handwritten letters and got 24 right. How many did it get wrong?
17. 17.📋 Planning an AI project: which comes first — set aside test photos or calculate percent right? (a) set aside test photos (b) calculate percent right
18. 18.🎯 Ishaan’s bird-song app is 70% accurate. If it is tested on 10 new bird songs, how many should it get right?
19. 19.📋 Planning an AI project: which comes first — label each example or pick a question to solve? (a) label each example (b) pick a question to solve
20. 20.🎯 Nisha’s recycling sorter is 50% accurate. If it is tested on 10 new waste photos, how many should it get right?
21. 21.🎯 Ananya’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
22. 22.📋 Planning an AI project: which comes first — work out the accuracy or test on new photos? (a) work out the accuracy (b) test on new photos
23. 23.📋 Planning an AI project: which comes first — fix it and test again or work out the accuracy? (a) fix it and test again (b) work out the accuracy
24. 24.🎯 Aarav’s leaf identifier is 80% accurate. If it is tested on 10 new leaf photos, how many should it get right?
25. 25.📋 Planning an AI project: which comes first — collect fruit photos or pick a question to solve? (a) collect fruit photos (b) pick a question to solve
26. 26.🎯 Aarav’s fruit sorter was tested on 10 new fruit photos and got 6 right. What is its accuracy in percent?
27. 27.📋 Planning an AI project: which comes first — split train and test or correct bad labels? (a) split train and test (b) correct bad labels
28. 28.📋 Planning an AI project: which comes first — test on new photos or split train and test? (a) test on new photos (b) split train and test
29. 29.❌ Arjun’s fruit sorter was tested on 15 new fruit photos and got 13 right. How many did it get wrong?
30. 30.❌ Arjun’s fruit sorter was tested on 15 new fruit photos and got 12 right. How many did it get wrong?
31. 31.🎯 Meera’s fruit sorter was tested on 4 new fruit photos and got 3 right. What is its accuracy in percent?
32. 32.📋 Planning an AI project: which comes first — calculate percent right or improve data, retest? (a) calculate percent right (b) improve data, retest
33. 33.🎯 Saanvi’s leaf identifier is 70% accurate. If it is tested on 40 new leaf photos, how many should it get right?
34. 34.📋 Planning an AI project: which comes first — try unseen examples or split train and test? (a) try unseen examples (b) split train and test
35. 35.📋 Planning an AI project: which comes first — test on new photos or fix it and test again? (a) test on new photos (b) fix it and test again
36. 36.📋 Planning an AI project: which comes first — train the model or gather many examples? (a) train the model (b) gather many examples
37. 37.🎯 Arjun’s leaf identifier is 50% accurate. If it is tested on 60 new leaf photos, how many should it get right?
38. 38.📋 Planning an AI project: which comes first — try unseen examples or choose what to sort? (a) try unseen examples (b) choose what to sort
39. 39.🎯 Nisha’s recycling sorter is 50% accurate. If it is tested on 60 new waste photos, how many should it get right?
40. 40.❌ Saanvi’s bird-song app was tested on 35 new bird songs and got 28 right. How many did it get wrong?

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