Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 506 · 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.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct ÷ total × 100 (d) correct + total
2. 2.📋 Planning an AI project: which comes first — pick a question to solve or set aside test photos? (a) pick a question to solve (b) set aside test photos
3. 3.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) more labelled examples (c) fewer examples (d) a louder speaker
4. 4.📋 Planning an AI project: which comes first — calculate percent right or train the model? (a) calculate percent right (b) train the model
5. 5.🎯 Ananya’s fruit sorter was tested on 5 new fruit photos and got 4 right. What is its accuracy in percent?
6. 6.📋 Planning an AI project: which comes first — improve data, retest or recheck every label? (a) improve data, retest (b) recheck every label
7. 7.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 43 right and Model B got 38 right. How many percentage points more accurate is Model A?
8. 8.📦 Meera collected 190 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
9. 9.📋 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
10. 10.🎯 Kabir’s recycling sorter was tested on 25 new waste photos and got 14 right. What is its accuracy in percent?
11. 11.📋 Planning an AI project: which comes first — gather many examples or fix it and test again? (a) gather many examples (b) fix it and test again
12. 12.📋 Planning an AI project: which comes first — pick a question to solve or calculate percent right? (a) pick a question to solve (b) calculate percent right
13. 13.📦 Kabir collected 60 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
14. 14.🧪 You can plan a simple AI project with… (a) nothing at all (b) only a big robot (c) paper and examples (d) a secret password
15. 15.❌ Nisha’s bird-song app was tested on 38 new bird songs and got 31 right. How many did it get wrong?
16. 16.⚖️ Two leaf identifier models were tested on the same 25 leaf photos. Model A got 20 right and Model B got 14 right. How many percentage points more accurate is Model A?
17. 17.🎯 Nisha’s leaf identifier is 50% accurate. If it is tested on 100 new leaf photos, how many should it get right?
18. 18.📋 Planning an AI project: which comes first — let it learn patterns or recheck every label? (a) let it learn patterns (b) recheck every label
19. 19.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 50 right and Model B got 49 right. How many percentage points more accurate is Model A?
20. 20.🎯 Vihaan’s recycling sorter is 70% accurate. If it is tested on 70 new waste photos, how many should it get right?
21. 21.📦 Vihaan collected 140 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
22. 22.📋 Planning an AI project: which comes first — label each example or choose what to sort? (a) label each example (b) choose what to sort
23. 23.📦 Meera collected 70 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
24. 24.📋 Planning an AI project: which comes first — split train and test or choose what to sort? (a) split train and test (b) choose what to sort
25. 25.🧪 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
26. 26.❌ Aarav’s leaf identifier was tested on 36 new leaf photos and got 30 right. How many did it get wrong?
27. 27.🎯 Nisha’s recycling sorter is 60% accurate. If it is tested on 30 new waste photos, how many should it get right?
28. 28.📋 Planning an AI project: which comes first — test on new photos or set aside test photos? (a) test on new photos (b) set aside test photos
29. 29.📋 Planning an AI project: which comes first — label each example or let it learn patterns? (a) label each example (b) let it learn patterns
30. 30.📋 Planning an AI project: which comes first — recheck every label or label each example? (a) recheck every label (b) label each example
31. 31.📦 Tara collected 160 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
32. 32.📋 Planning an AI project: which comes first — set aside test photos or try unseen examples? (a) set aside test photos (b) try unseen examples
33. 33.📋 Planning an AI project: which comes first — correct bad labels or fix it and test again? (a) correct bad labels (b) fix it and test again
34. 34.📋 Planning an AI project: which comes first — tag each photo by type or choose what to sort? (a) tag each photo by type (b) choose what to sort
35. 35.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
36. 36.🎯 Meera’s leaf identifier was tested on 5 new leaf photos and got 4 right. What is its accuracy in percent?
37. 37.🎯 Ananya’s fruit sorter is 90% accurate. If it is tested on 70 new fruit photos, how many should it get right?
38. 38.❌ Ananya’s handwriting reader was tested on 32 new handwritten letters and got 24 right. How many did it get wrong?
39. 39.📋 Planning an AI project: which comes first — test on new photos or improve data, retest? (a) test on new photos (b) improve data, retest
40. 40.📋 Planning an AI project: which comes first — train the model or recheck every label? (a) train the model (b) recheck every label

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