Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 327 · 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.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to make it bigger (c) to see if it learned (d) to save paper
2. 2.❌ Ishaan’s leaf identifier was tested on 17 new leaf photos and got 12 right. How many did it get wrong?
3. 3.📋 Planning an AI project: which comes first — fix it and test again or calculate percent right? (a) fix it and test again (b) calculate percent right
4. 4.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
5. 5.❌ Aarav’s leaf identifier was tested on 37 new leaf photos and got 28 right. How many did it get wrong?
6. 6.📦 Rohan collected 80 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
7. 7.📋 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
8. 8.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 30 right and Model B got 26 right. How many percentage points more accurate is Model A?
9. 9.🎯 Aarav’s leaf identifier is 80% accurate. If it is tested on 80 new leaf photos, how many should it get right?
10. 10.🎯 Aarav’s bird-song app is 90% accurate. If it is tested on 60 new bird songs, how many should it get right?
11. 11.❌ Diya’s fruit sorter was tested on 20 new fruit photos and got 14 right. How many did it get wrong?
12. 12.🎯 Kabir’s fruit sorter was tested on 25 new fruit photos and got 21 right. What is its accuracy in percent?
13. 13.🎯 Meera’s recycling sorter was tested on 5 new waste photos and got 5 right. What is its accuracy in percent?
14. 14.📦 Kabir collected 80 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
15. 15.❌ Tara’s spam spotter was tested on 18 new messages and got 13 right. How many did it get wrong?
16. 16.🎯 Ishaan’s recycling sorter is 50% accurate. If it is tested on 70 new waste photos, how many should it get right?
17. 17.❌ Kabir’s bird-song app was tested on 44 new bird songs and got 43 right. How many did it get wrong?
18. 18.📋 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
19. 19.🎯 Kabir’s recycling sorter is 60% accurate. If it is tested on 80 new waste photos, how many should it get right?
20. 20.📋 Planning an AI project: which comes first — collect fruit photos or set aside test photos? (a) collect fruit photos (b) set aside test photos
21. 21.🎯 Saanvi’s leaf identifier is 60% accurate. If it is tested on 90 new leaf photos, how many should it get right?
22. 22.📋 Planning an AI project: which comes first — improve data, retest or collect fruit photos? (a) improve data, retest (b) collect fruit photos
23. 23.❌ Nisha’s bird-song app was tested on 23 new bird songs and got 18 right. How many did it get wrong?
24. 24.🧪 What is accuracy? (a) total − correct (b) correct ÷ total × 100 (c) correct + total (d) total × 2
25. 25.📦 Kabir collected 40 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
26. 26.🎯 Saanvi’s recycling sorter was tested on 20 new waste photos and got 14 right. What is its accuracy in percent?
27. 27.📦 Tara collected 130 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
28. 28.📋 Planning an AI project: which comes first — correct bad labels or test on new photos? (a) correct bad labels (b) test on new photos
29. 29.📋 Planning an AI project: which comes first — try unseen examples or let it learn patterns? (a) try unseen examples (b) let it learn patterns
30. 30.❌ Tara’s recycling sorter was tested on 27 new waste photos and got 18 right. How many did it get wrong?
31. 31.📋 Planning an AI project: which comes first — try unseen examples or split train and test? (a) try unseen examples (b) split train and test
32. 32.🧪 You can plan a simple AI project with… (a) paper and examples (b) a secret password (c) nothing at all (d) only a big robot
33. 33.📋 Planning an AI project: which comes first — pick a question to solve or improve data, retest? (a) pick a question to solve (b) improve data, retest
34. 34.📦 Meera collected 170 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
35. 35.📋 Planning an AI project: which comes first — label each example or choose what to sort? (a) label each example (b) choose what to sort
36. 36.📦 Tara collected 130 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
37. 37.📋 Planning an AI project: which comes first — correct bad labels or calculate percent right? (a) correct bad labels (b) calculate percent right
38. 38.🎯 Vihaan’s fruit sorter was tested on 10 new fruit photos and got 5 right. What is its accuracy in percent?
39. 39.📋 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
40. 40.📋 Planning an AI project: which comes first — work out the accuracy or gather many examples? (a) work out the accuracy (b) gather many examples

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