Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 77 · 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 — correct bad labels or work out the accuracy? (a) correct bad labels (b) work out the accuracy
2. 2.🧪 You can plan a simple AI project with… (a) paper and examples (b) a secret password (c) only a big robot (d) nothing at all
3. 3.📦 Kabir collected 70 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
4. 4.📋 Planning an AI project: which comes first — set aside test photos or improve data, retest? (a) set aside test photos (b) improve data, retest
5. 5.📋 Planning an AI project: which comes first — try unseen examples or improve data, retest? (a) try unseen examples (b) improve data, retest
6. 6.📦 Vihaan collected 200 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
7. 7.📋 Planning an AI project: which comes first — label each example or test on new photos? (a) label each example (b) test on new photos
8. 8.📋 Planning an AI project: which comes first — gather many examples or calculate percent right? (a) gather many examples (b) calculate percent right
9. 9.📋 Planning an AI project: which comes first — calculate percent right or gather many examples? (a) calculate percent right (b) gather many examples
10. 10.🎯 Ishaan’s leaf identifier was tested on 50 new leaf photos and got 40 right. What is its accuracy in percent?
11. 11.📦 Ananya collected 180 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
12. 12.❌ Diya’s handwriting reader was tested on 49 new handwritten letters and got 46 right. How many did it get wrong?
13. 13.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to make it faster (c) to see if it learned (d) to save paper
14. 14.📋 Planning an AI project: which comes first — split train and test or work out the accuracy? (a) split train and test (b) work out the accuracy
15. 15.📋 Planning an AI project: which comes first — pick a question to solve or correct bad labels? (a) pick a question to solve (b) correct bad labels
16. 16.📋 Planning an AI project: which comes first — train the model or choose what to sort? (a) train the model (b) choose what to sort
17. 17.🎯 Vihaan’s handwriting reader is 60% accurate. If it is tested on 40 new handwritten letters, how many should it get right?
18. 18.📦 Ananya collected 90 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
19. 19.📋 Planning an AI project: which comes first — calculate percent right or test on new photos? (a) calculate percent right (b) test on new photos
20. 20.🧪 What is accuracy? (a) total × 2 (b) correct ÷ total × 100 (c) total − correct (d) correct + total
21. 21.📋 Planning an AI project: which comes first — recheck every label or collect fruit photos? (a) recheck every label (b) collect fruit photos
22. 22.📋 Planning an AI project: which comes first — test on new photos or train the model? (a) test on new photos (b) train the model
23. 23.📦 Vihaan collected 100 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
24. 24.📋 Planning an AI project: which comes first — improve data, retest or test on new photos? (a) improve data, retest (b) test on new photos
25. 25.📋 Planning an AI project: which comes first — let it learn patterns or calculate percent right? (a) let it learn patterns (b) calculate percent right
26. 26.📋 Planning an AI project: which comes first — let it learn patterns or split train and test? (a) let it learn patterns (b) split train and test
27. 27.❌ Ishaan’s fruit sorter was tested on 32 new fruit photos and got 31 right. How many did it get wrong?
28. 28.📋 Planning an AI project: which comes first — label each example or improve data, retest? (a) label each example (b) improve data, retest
29. 29.🎯 Saanvi’s leaf identifier is 60% accurate. If it is tested on 20 new leaf photos, how many should it get right?
30. 30.📦 Tara collected 60 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
31. 31.📋 Planning an AI project: which comes first — calculate percent right or fix it and test again? (a) calculate percent right (b) fix it and test again
32. 32.📋 Planning an AI project: which comes first — train the model or correct bad labels? (a) train the model (b) correct bad labels
33. 33.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) a new colour screen (c) more labelled examples (d) fewer examples
34. 34.📋 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
35. 35.📋 Planning an AI project: which comes first — tag each photo by type or recheck every label? (a) tag each photo by type (b) recheck every label
36. 36.❌ Aarav’s recycling sorter was tested on 22 new waste photos and got 14 right. How many did it get wrong?
37. 37.📦 Aarav collected 80 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
38. 38.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
39. 39.📋 Planning an AI project: which comes first — tag each photo by type or set aside test photos? (a) tag each photo by type (b) set aside test photos
40. 40.❌ Saanvi’s spam spotter was tested on 39 new messages and got 31 right. How many did it get wrong?

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