Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 322 · 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 — fix it and test again or try unseen examples? (a) fix it and test again (b) try unseen examples
2. 2.📋 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
3. 3.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) a louder speaker (c) fewer examples (d) more labelled examples
4. 4.📦 Diya collected 90 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
5. 5.📋 Planning an AI project: which comes first — collect fruit photos or choose what to sort? (a) collect fruit photos (b) choose what to sort
6. 6.📋 Planning an AI project: which comes first — label each example or correct bad labels? (a) label each example (b) correct bad labels
7. 7.❌ Rohan’s spam spotter was tested on 22 new messages and got 19 right. How many did it get wrong?
8. 8.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
9. 9.🧪 What is accuracy? (a) correct + total (b) total × 2 (c) total − correct (d) correct ÷ total × 100
10. 10.📋 Planning an AI project: which comes first — fix it and test again or recheck every label? (a) fix it and test again (b) recheck every label
11. 11.🎯 Rohan’s leaf identifier is 60% accurate. If it is tested on 100 new leaf photos, how many should it get right?
12. 12.🎯 Ananya’s bird-song app was tested on 25 new bird songs and got 22 right. What is its accuracy in percent?
13. 13.🎯 Aarav’s bird-song app is 70% accurate. If it is tested on 40 new bird songs, how many should it get right?
14. 14.🎯 Nisha’s recycling sorter is 80% accurate. If it is tested on 100 new waste photos, how many should it get right?
15. 15.🧪 You can plan a simple AI project with… (a) nothing at all (b) a secret password (c) paper and examples (d) only a big robot
16. 16.❌ Kabir’s bird-song app was tested on 34 new bird songs and got 29 right. How many did it get wrong?
17. 17.🎯 Ishaan’s fruit sorter was tested on 20 new fruit photos and got 20 right. What is its accuracy in percent?
18. 18.📋 Planning an AI project: which comes first — tag each photo by type or correct bad labels? (a) tag each photo by type (b) correct bad labels
19. 19.🎯 Nisha’s recycling sorter was tested on 4 new waste photos and got 3 right. What is its accuracy in percent?
20. 20.📋 Planning an AI project: which comes first — work out the accuracy or train the model? (a) work out the accuracy (b) train the model
21. 21.❌ Aarav’s fruit sorter was tested on 24 new fruit photos and got 20 right. How many did it get wrong?
22. 22.🎯 Kabir’s recycling sorter is 60% accurate. If it is tested on 90 new waste photos, how many should it get right?
23. 23.🎯 Kabir’s fruit sorter is 70% accurate. If it is tested on 50 new fruit photos, how many should it get right?
24. 24.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 7 right and Model B got 5 right. How many percentage points more accurate is Model A?
25. 25.📦 Aarav collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
26. 26.❌ Kabir’s spam spotter was tested on 35 new messages and got 32 right. How many did it get wrong?
27. 27.📋 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
28. 28.📋 Planning an AI project: which comes first — collect fruit photos or train the model? (a) collect fruit photos (b) train the model
29. 29.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
30. 30.📋 Planning an AI project: which comes first — try unseen examples or fix it and test again? (a) try unseen examples (b) fix it and test again
31. 31.❌ Aarav’s leaf identifier was tested on 19 new leaf photos and got 11 right. How many did it get wrong?
32. 32.📋 Planning an AI project: which comes first — work out the accuracy or fix it and test again? (a) work out the accuracy (b) fix it and test again
33. 33.📋 Planning an AI project: which comes first — set aside test photos or improve data, retest? (a) set aside test photos (b) improve data, retest
34. 34.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 47 right and Model B got 29 right. How many percentage points more accurate is Model A?
35. 35.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 20 right and Model B got 14 right. How many percentage points more accurate is Model A?
36. 36.🎯 Kabir’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
37. 37.❌ Meera’s handwriting reader was tested on 30 new handwritten letters and got 21 right. How many did it get wrong?
38. 38.📋 Planning an AI project: which comes first — fix it and test again or collect fruit photos? (a) fix it and test again (b) collect fruit photos
39. 39.🧪 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 faster (d) to make it bigger
40. 40.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 36 right and Model B got 34 right. How many percentage points more accurate is Model A?

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