Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 348 · 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 — train the model or pick a question to solve? (a) train the model (b) pick a question to solve
2. 2.📋 Planning an AI project: which comes first — recheck every label or set aside test photos? (a) recheck every label (b) set aside test photos
3. 3.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) a louder speaker (c) fewer examples (d) a new colour screen
4. 4.🎯 Diya’s spam spotter was tested on 50 new messages and got 35 right. What is its accuracy in percent?
5. 5.⚖️ Two leaf identifier models were tested on the same 20 leaf photos. Model A got 16 right and Model B got 14 right. How many percentage points more accurate is Model A?
6. 6.🎯 Arjun’s leaf identifier is 50% accurate. If it is tested on 70 new leaf photos, how many should it get right?
7. 7.🎯 Aarav’s spam spotter was tested on 50 new messages and got 47 right. What is its accuracy in percent?
8. 8.📋 Planning an AI project: which comes first — work out the accuracy or set aside test photos? (a) work out the accuracy (b) set aside test photos
9. 9.📋 Planning an AI project: which comes first — tag each photo by type or split train and test? (a) tag each photo by type (b) split train and test
10. 10.📦 Meera collected 70 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
11. 11.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct ÷ total × 100 (d) correct + total
12. 12.❌ Tara’s handwriting reader was tested on 22 new handwritten letters and got 15 right. How many did it get wrong?
13. 13.🎯 Arjun’s leaf identifier is 70% accurate. If it is tested on 70 new leaf photos, how many should it get right?
14. 14.❌ Kabir’s spam spotter was tested on 38 new messages and got 32 right. How many did it get wrong?
15. 15.🎯 Diya’s spam spotter is 80% accurate. If it is tested on 70 new messages, how many should it get right?
16. 16.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to see if it learned (c) to save paper (d) to make it faster
17. 17.🎯 Diya’s spam spotter was tested on 25 new messages and got 25 right. What is its accuracy in percent?
18. 18.📋 Planning an AI project: which comes first — correct bad labels or pick a question to solve? (a) correct bad labels (b) pick a question to solve
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.⚖️ Two bird-song app models were tested on the same 25 bird songs. Model A got 24 right and Model B got 23 right. How many percentage points more accurate is Model A?
21. 21.❌ Ananya’s spam spotter was tested on 19 new messages and got 14 right. How many did it get wrong?
22. 22.🎯 Diya’s fruit sorter is 60% accurate. If it is tested on 70 new fruit photos, how many should it get right?
23. 23.📦 Aarav collected 110 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
24. 24.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 23 right and Model B got 15 right. How many percentage points more accurate is Model A?
25. 25.📦 Kabir collected 50 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
26. 26.🎯 Diya’s recycling sorter was tested on 25 new waste photos and got 21 right. What is its accuracy in percent?
27. 27.📋 Planning an AI project: which comes first — correct bad labels or gather many examples? (a) correct bad labels (b) gather many examples
28. 28.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
29. 29.📋 Planning an AI project: which comes first — fix it and test again or let it learn patterns? (a) fix it and test again (b) let it learn patterns
30. 30.📋 Planning an AI project: which comes first — recheck every label or fix it and test again? (a) recheck every label (b) fix it and test again
31. 31.❌ Ananya’s fruit sorter was tested on 47 new fruit photos and got 46 right. How many did it get wrong?
32. 32.❌ Vihaan’s spam spotter was tested on 45 new messages and got 43 right. How many did it get wrong?
33. 33.🎯 Diya’s recycling sorter is 80% accurate. If it is tested on 20 new waste photos, how many should it get right?
34. 34.📋 Planning an AI project: which comes first — collect fruit photos or recheck every label? (a) collect fruit photos (b) recheck every label
35. 35.📋 Planning an AI project: which comes first — recheck every label or split train and test? (a) recheck every label (b) split train and test
36. 36.🎯 Vihaan’s leaf identifier was tested on 20 new leaf photos and got 13 right. What is its accuracy in percent?
37. 37.❌ Aarav’s leaf identifier was tested on 28 new leaf photos and got 21 right. How many did it get wrong?
38. 38.📋 Planning an AI project: which comes first — test on new photos or label each example? (a) test on new photos (b) label each example
39. 39.📋 Planning an AI project: which comes first — let it learn patterns or recheck every label? (a) let it learn patterns (b) recheck every label
40. 40.🎯 Vihaan’s handwriting reader is 70% accurate. If it is tested on 70 new handwritten letters, how many should it get right?

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