Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 496 · 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.❌ Nisha’s spam spotter was tested on 46 new messages and got 43 right. How many did it get wrong?
2. 2.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it bigger (c) to make it faster (d) to see if it learned
3. 3.📋 Planning an AI project: which comes first — let it learn patterns or try unseen examples? (a) let it learn patterns (b) try unseen examples
4. 4.❌ Ananya’s fruit sorter was tested on 34 new fruit photos and got 28 right. How many did it get wrong?
5. 5.📋 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
6. 6.📋 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
7. 7.📋 Planning an AI project: which comes first — recheck every label or split train and test? (a) recheck every label (b) split train and test
8. 8.🎯 Nisha’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
9. 9.📦 Saanvi collected 60 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
10. 10.🧪 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
11. 11.🎯 Ananya’s leaf identifier was tested on 20 new leaf photos and got 20 right. What is its accuracy in percent?
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.📋 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
14. 14.🎯 Aarav’s leaf identifier was tested on 4 new leaf photos and got 2 right. What is its accuracy in percent?
15. 15.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 20 right and Model B got 17 right. How many percentage points more accurate is Model A?
16. 16.📋 Planning an AI project: which comes first — correct bad labels or split train and test? (a) correct bad labels (b) split train and test
17. 17.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 11 right and Model B got 10 right. How many percentage points more accurate is Model A?
18. 18.🎯 Rohan’s bird-song app is 70% accurate. If it is tested on 90 new bird songs, how many should it get right?
19. 19.🎯 Meera’s leaf identifier is 90% accurate. If it is tested on 40 new leaf photos, how many should it get right?
20. 20.📦 Meera collected 150 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
21. 21.❌ Nisha’s handwriting reader was tested on 13 new handwritten letters and got 11 right. How many did it get wrong?
22. 22.📋 Planning an AI project: which comes first — train the model or work out the accuracy? (a) train the model (b) work out the accuracy
23. 23.🧪 What is accuracy? (a) total × 2 (b) correct + total (c) total − correct (d) correct ÷ total × 100
24. 24.🧪 You can plan a simple AI project with… (a) nothing at all (b) paper and examples (c) a secret password (d) only a big robot
25. 25.📋 Planning an AI project: which comes first — let it learn patterns or tag each photo by type? (a) let it learn patterns (b) tag each photo by type
26. 26.📋 Planning an AI project: which comes first — fix it and test again or work out the accuracy? (a) fix it and test again (b) work out the accuracy
27. 27.❌ Aarav’s recycling sorter was tested on 20 new waste photos and got 18 right. How many did it get wrong?
28. 28.🎯 Meera’s fruit sorter was tested on 20 new fruit photos and got 19 right. What is its accuracy in percent?
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.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 22 right and Model B got 21 right. How many percentage points more accurate is Model A?
31. 31.📋 Planning an AI project: which comes first — label each example or work out the accuracy? (a) label each example (b) work out the accuracy
32. 32.🎯 Aarav’s leaf identifier was tested on 50 new leaf photos and got 35 right. What is its accuracy in percent?
33. 33.🎯 Aarav’s bird-song app was tested on 50 new bird songs and got 38 right. What is its accuracy in percent?
34. 34.📋 Planning an AI project: which comes first — correct bad labels or let it learn patterns? (a) correct bad labels (b) let it learn patterns
35. 35.❌ Nisha’s fruit sorter was tested on 30 new fruit photos and got 26 right. How many did it get wrong?
36. 36.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
37. 37.❌ Kabir’s fruit sorter was tested on 43 new fruit photos and got 37 right. How many did it get wrong?
38. 38.📋 Planning an AI project: which comes first — pick a question to solve or fix it and test again? (a) pick a question to solve (b) fix it and test again
39. 39.📋 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
40. 40.❌ Diya’s bird-song app was tested on 46 new bird songs and got 38 right. How many did it get wrong?

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