Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 166 · 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 — test on new photos or pick a question to solve? (a) test on new photos (b) pick a question to solve
2. 2.📋 Planning an AI project: which comes first — collect fruit photos or train the model? (a) collect fruit photos (b) train the model
3. 3.❌ Aarav’s leaf identifier was tested on 33 new leaf photos and got 26 right. How many did it get wrong?
4. 4.📋 Planning an AI project: which comes first — calculate percent right or label each example? (a) calculate percent right (b) label each example
5. 5.📋 Planning an AI project: which comes first — calculate percent right or split train and test? (a) calculate percent right (b) split train and test
6. 6.❌ Tara’s leaf identifier was tested on 41 new leaf photos and got 34 right. How many did it get wrong?
7. 7.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it faster (c) to see if it learned (d) to make it bigger
8. 8.⚖️ 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?
9. 9.📋 Planning an AI project: which comes first — split train and test or fix it and test again? (a) split train and test (b) fix it and test again
10. 10.🎯 Rohan’s fruit sorter was tested on 25 new fruit photos and got 23 right. What is its accuracy in percent?
11. 11.🧪 You can plan a simple AI project with… (a) only a big robot (b) a secret password (c) paper and examples (d) nothing at all
12. 12.🎯 Meera’s fruit sorter was tested on 20 new fruit photos and got 18 right. What is its accuracy in percent?
13. 13.📋 Planning an AI project: which comes first — choose what to sort or tag each photo by type? (a) choose what to sort (b) tag each photo by type
14. 14.📋 Planning an AI project: which comes first — split train and test or collect fruit photos? (a) split train and test (b) collect fruit photos
15. 15.📋 Planning an AI project: which comes first — label each example or improve data, retest? (a) label each example (b) improve data, retest
16. 16.🎯 Saanvi’s recycling sorter was tested on 25 new waste photos and got 17 right. What is its accuracy in percent?
17. 17.🎯 Arjun’s bird-song app was tested on 50 new bird songs and got 33 right. What is its accuracy in percent?
18. 18.🎯 Arjun’s recycling sorter was tested on 5 new waste photos and got 4 right. What is its accuracy in percent?
19. 19.🧪 What is accuracy? (a) correct + total (b) correct ÷ total × 100 (c) total − correct (d) total × 2
20. 20.📋 Planning an AI project: which comes first — gather many examples or improve data, retest? (a) gather many examples (b) improve data, retest
21. 21.📋 Planning an AI project: which comes first — improve data, retest or recheck every label? (a) improve data, retest (b) recheck every label
22. 22.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 50 right and Model B got 48 right. How many percentage points more accurate is Model A?
23. 23.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
24. 24.⚖️ Two recycling sorter models were tested on the same 20 waste photos. Model A got 20 right and Model B got 19 right. How many percentage points more accurate is Model A?
25. 25.📋 Planning an AI project: which comes first — test on new photos or correct bad labels? (a) test on new photos (b) correct bad labels
26. 26.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) a louder speaker (c) fewer examples (d) more labelled examples
27. 27.🎯 Vihaan’s handwriting reader was tested on 10 new handwritten letters and got 6 right. What is its accuracy in percent?
28. 28.📋 Planning an AI project: which comes first — calculate percent right or improve data, retest? (a) calculate percent right (b) improve data, retest
29. 29.📋 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
30. 30.📦 Aarav collected 40 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 — choose what to sort or correct bad labels? (a) choose what to sort (b) correct bad labels
32. 32.📋 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
33. 33.🎯 Arjun’s spam spotter is 50% accurate. If it is tested on 80 new messages, how many should it get right?
34. 34.📋 Planning an AI project: which comes first — work out the accuracy or collect fruit photos? (a) work out the accuracy (b) collect fruit photos
35. 35.🎯 Aarav’s spam spotter is 80% accurate. If it is tested on 80 new messages, how many should it get right?
36. 36.📋 Planning an AI project: which comes first — choose what to sort or improve data, retest? (a) choose what to sort (b) improve data, retest
37. 37.🎯 Kabir’s fruit sorter was tested on 20 new fruit photos and got 10 right. What is its accuracy in percent?
38. 38.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 18 right and Model B got 17 right. How many percentage points more accurate is Model A?
39. 39.🎯 Kabir’s recycling sorter is 50% accurate. If it is tested on 20 new waste photos, how many should it get right?
40. 40.❌ Diya’s bird-song app was tested on 40 new bird songs and got 33 right. How many did it get wrong?

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