Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 290 · 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.📦 Diya collected 40 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
2. 2.⚖️ Two leaf identifier models were tested on the same 20 leaf photos. Model A got 16 right and Model B got 11 right. How many percentage points more accurate is Model A?
3. 3.📋 Planning an AI project: which comes first — train the model or split train and test? (a) train the model (b) split train and test
4. 4.🎯 Nisha’s fruit sorter is 60% accurate. If it is tested on 40 new fruit photos, how many should it get right?
5. 5.🎯 Nisha’s recycling sorter was tested on 50 new waste photos and got 31 right. What is its accuracy in percent?
6. 6.📋 Planning an AI project: which comes first — collect fruit photos or recheck every label? (a) collect fruit photos (b) recheck every label
7. 7.❌ Arjun’s recycling sorter was tested on 50 new waste photos and got 43 right. How many did it get wrong?
8. 8.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct ÷ total × 100 (d) correct + total
9. 9.🎯 Rohan’s recycling sorter is 60% accurate. If it is tested on 30 new waste photos, how many should it get right?
10. 10.📦 Ananya collected 180 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
11. 11.🎯 Tara’s spam spotter is 60% accurate. If it is tested on 10 new messages, how many should it get right?
12. 12.📦 Aarav collected 200 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
13. 13.📋 Planning an AI project: which comes first — gather many examples or try unseen examples? (a) gather many examples (b) try unseen examples
14. 14.📦 Ananya collected 80 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
15. 15.📋 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
16. 16.📋 Planning an AI project: which comes first — gather many examples or correct bad labels? (a) gather many examples (b) correct bad labels
17. 17.🧪 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
18. 18.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 25 right and Model B got 16 right. How many percentage points more accurate is Model A?
19. 19.🎯 Diya’s fruit sorter is 90% accurate. If it is tested on 90 new fruit photos, how many should it get right?
20. 20.📋 Planning an AI project: which comes first — recheck every label or improve data, retest? (a) recheck every label (b) improve data, retest
21. 21.📋 Planning an AI project: which comes first — choose what to sort or improve data, retest? (a) choose what to sort (b) improve data, retest
22. 22.📋 Planning an AI project: which comes first — fix it and test again or set aside test photos? (a) fix it and test again (b) set aside test photos
23. 23.❌ Ananya’s bird-song app was tested on 18 new bird songs and got 16 right. How many did it get wrong?
24. 24.📦 Rohan collected 60 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
25. 25.📦 Tara collected 60 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
26. 26.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 42 right and Model B got 36 right. How many percentage points more accurate is Model A?
27. 27.🎯 Rohan’s spam spotter is 80% accurate. If it is tested on 90 new messages, how many should it get right?
28. 28.🎯 Aarav’s spam spotter is 80% accurate. If it is tested on 10 new messages, how many should it get right?
29. 29.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 10 right and Model B got 6 right. How many percentage points more accurate is Model A?
30. 30.🎯 Diya’s fruit sorter was tested on 10 new fruit photos and got 7 right. What is its accuracy in percent?
31. 31.📦 Ishaan collected 60 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
32. 32.📦 Arjun collected 70 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
33. 33.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 12 right and Model B got 11 right. How many percentage points more accurate is Model A?
34. 34.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 10 right and Model B got 7 right. How many percentage points more accurate is Model A?
35. 35.🧪 You can plan a simple AI project with… (a) only a big robot (b) nothing at all (c) paper and examples (d) a secret password
36. 36.⚖️ Two bird-song app models were tested on the same 25 bird songs. Model A got 16 right and Model B got 15 right. How many percentage points more accurate is Model A?
37. 37.🧪 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
38. 38.🎯 Diya’s bird-song app was tested on 20 new bird songs and got 17 right. What is its accuracy in percent?
39. 39.📋 Planning an AI project: which comes first — calculate percent right or label each example? (a) calculate percent right (b) label each example
40. 40.🎯 Kabir’s handwriting reader is 70% accurate. If it is tested on 20 new handwritten letters, how many should it get right?

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