Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 974 · 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 recheck every label? (a) calculate percent right (b) recheck every label
2. 2.📋 Planning an AI project: which comes first — recheck every label or gather many examples? (a) recheck every label (b) gather many examples
3. 3.🎯 Ishaan’s leaf identifier is 50% accurate. If it is tested on 60 new leaf photos, how many should it get right?
4. 4.📋 Planning an AI project: which comes first — gather many examples or try unseen examples? (a) gather many examples (b) try unseen examples
5. 5.🎯 Ananya’s handwriting reader is 60% accurate. If it is tested on 20 new handwritten letters, how many should it get right?
6. 6.🧪 What is accuracy? (a) total − correct (b) correct + total (c) correct ÷ total × 100 (d) total × 2
7. 7.🎯 Tara’s fruit sorter is 60% accurate. If it is tested on 70 new fruit photos, how many should it get right?
8. 8.📋 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
9. 9.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) fewer examples (c) a new colour screen (d) a louder speaker
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.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to save paper (c) to make it bigger (d) to make it faster
12. 12.📋 Planning an AI project: which comes first — train the model or split train and test? (a) train the model (b) split train and test
13. 13.❌ Aarav’s spam spotter was tested on 28 new messages and got 23 right. How many did it get wrong?
14. 14.📋 Planning an AI project: which comes first — improve data, retest or set aside test photos? (a) improve data, retest (b) set aside test photos
15. 15.🎯 Diya’s bird-song app was tested on 25 new bird songs and got 17 right. What is its accuracy in percent?
16. 16.📦 Arjun collected 190 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
17. 17.📦 Ishaan collected 60 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
18. 18.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 20 right and Model B got 18 right. How many percentage points more accurate is Model A?
19. 19.📋 Planning an AI project: which comes first — train the model or correct bad labels? (a) train the model (b) correct bad labels
20. 20.🧪 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
21. 21.🎯 Diya’s recycling sorter was tested on 50 new waste photos and got 47 right. What is its accuracy in percent?
22. 22.❌ Arjun’s recycling sorter was tested on 22 new waste photos and got 15 right. How many did it get wrong?
23. 23.❌ Ishaan’s recycling sorter was tested on 29 new waste photos and got 24 right. How many did it get wrong?
24. 24.❌ Diya’s fruit sorter was tested on 46 new fruit photos and got 44 right. How many did it get wrong?
25. 25.📋 Planning an AI project: which comes first — recheck every label or split train and test? (a) recheck every label (b) split train and test
26. 26.🎯 Tara’s recycling sorter was tested on 4 new waste photos and got 3 right. What is its accuracy in percent?
27. 27.🎯 Kabir’s leaf identifier was tested on 4 new leaf photos and got 3 right. What is its accuracy in percent?
28. 28.❌ Kabir’s fruit sorter was tested on 19 new fruit photos and got 14 right. How many did it get wrong?
29. 29.📋 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
30. 30.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 19 right and Model B got 13 right. How many percentage points more accurate is Model A?
31. 31.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 25 right and Model B got 23 right. How many percentage points more accurate is Model A?
32. 32.🎯 Saanvi’s bird-song app was tested on 5 new bird songs and got 3 right. What is its accuracy in percent?
33. 33.📋 Planning an AI project: which comes first — test on new photos or work out the accuracy? (a) test on new photos (b) work out the accuracy
34. 34.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 9 right and Model B got 6 right. How many percentage points more accurate is Model A?
35. 35.🎯 Diya’s handwriting reader is 90% accurate. If it is tested on 70 new handwritten letters, how many should it get right?
36. 36.🎯 Arjun’s leaf identifier was tested on 20 new leaf photos and got 16 right. What is its accuracy in percent?
37. 37.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 6 right and Model B got 5 right. How many percentage points more accurate is Model A?
38. 38.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
39. 39.🎯 Aarav’s recycling sorter was tested on 5 new waste photos and got 3 right. What is its accuracy in percent?
40. 40.❌ Vihaan’s bird-song app was tested on 22 new bird songs and got 19 right. How many did it get wrong?

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