Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 164 · 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 — calculate percent right or gather many examples? (a) calculate percent right (b) gather many examples
2. 2.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
3. 3.🎯 Aarav’s leaf identifier is 90% accurate. If it is tested on 10 new leaf photos, how many should it get right?
4. 4.📋 Planning an AI project: which comes first — pick a question to solve or let it learn patterns? (a) pick a question to solve (b) let it learn patterns
5. 5.🧪 What is accuracy? (a) correct ÷ total × 100 (b) total − correct (c) correct + total (d) total × 2
6. 6.📋 Planning an AI project: which comes first — recheck every label or choose what to sort? (a) recheck every label (b) choose what to sort
7. 7.🎯 Vihaan’s fruit sorter is 80% accurate. If it is tested on 30 new fruit photos, how many should it get right?
8. 8.🎯 Meera’s spam spotter was tested on 4 new messages and got 2 right. What is its accuracy in percent?
9. 9.📋 Planning an AI project: which comes first — try unseen examples or calculate percent right? (a) try unseen examples (b) calculate percent right
10. 10.📦 Meera collected 50 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
11. 11.🧪 You can plan a simple AI project with… (a) a secret password (b) only a big robot (c) paper and examples (d) nothing at all
12. 12.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 45 right and Model B got 39 right. How many percentage points more accurate is Model A?
13. 13.❌ Nisha’s fruit sorter was tested on 14 new fruit photos and got 12 right. How many did it get wrong?
14. 14.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) more labelled examples (c) a louder speaker (d) a new colour screen
15. 15.❌ Ishaan’s handwriting reader was tested on 42 new handwritten letters and got 40 right. How many did it get wrong?
16. 16.📋 Planning an AI project: which comes first — calculate percent right or try unseen examples? (a) calculate percent right (b) try unseen examples
17. 17.🎯 Vihaan’s fruit sorter was tested on 10 new fruit photos and got 7 right. What is its accuracy in percent?
18. 18.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to see if it learned (c) to make it bigger (d) to save paper
19. 19.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 8 right and Model B got 7 right. How many percentage points more accurate is Model A?
20. 20.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 50 right and Model B got 25 right. How many percentage points more accurate is Model A?
21. 21.❌ Kabir’s leaf identifier was tested on 47 new leaf photos and got 40 right. How many did it get wrong?
22. 22.📋 Planning an AI project: which comes first — correct bad labels or try unseen examples? (a) correct bad labels (b) try unseen examples
23. 23.📋 Planning an AI project: which comes first — gather many examples or improve data, retest? (a) gather many examples (b) improve data, retest
24. 24.🎯 Vihaan’s handwriting reader was tested on 5 new handwritten letters and got 5 right. What is its accuracy in percent?
25. 25.📋 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
26. 26.📋 Planning an AI project: which comes first — let it learn patterns or correct bad labels? (a) let it learn patterns (b) correct bad labels
27. 27.📋 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
28. 28.❌ Ananya’s recycling sorter was tested on 23 new waste photos and got 18 right. How many did it get wrong?
29. 29.❌ Tara’s spam spotter was tested on 25 new messages and got 19 right. How many did it get wrong?
30. 30.📦 Tara collected 180 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
31. 31.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
32. 32.📋 Planning an AI project: which comes first — work out the accuracy or try unseen examples? (a) work out the accuracy (b) try unseen examples
33. 33.🎯 Meera’s bird-song app was tested on 10 new bird songs and got 5 right. What is its accuracy in percent?
34. 34.🎯 Aarav’s spam spotter was tested on 4 new messages and got 3 right. What is its accuracy in percent?
35. 35.📋 Planning an AI project: which comes first — calculate percent right or split train and test? (a) calculate percent right (b) split train and test
36. 36.📦 Aarav collected 50 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
37. 37.📦 Kabir collected 50 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
38. 38.📦 Nisha collected 180 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
39. 39.📋 Planning an AI project: which comes first — tag each photo by type or collect fruit photos? (a) tag each photo by type (b) collect fruit photos
40. 40.🎯 Diya’s bird-song app was tested on 25 new bird songs and got 13 right. What is its accuracy in percent?

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