Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 679 · 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 — split train and test or test on new photos? (a) split train and test (b) test on new photos
2. 2.📦 Nisha collected 110 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
3. 3.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) fewer examples (c) a louder speaker (d) more labelled examples
4. 4.❌ Ananya’s recycling sorter was tested on 11 new waste photos and got 10 right. How many did it get wrong?
5. 5.📋 Planning an AI project: which comes first — train the model or recheck every label? (a) train the model (b) recheck every label
6. 6.📋 Planning an AI project: which comes first — work out the accuracy or let it learn patterns? (a) work out the accuracy (b) let it learn patterns
7. 7.📋 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
8. 8.🎯 Tara’s recycling sorter was tested on 50 new waste photos and got 42 right. What is its accuracy in percent?
9. 9.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 34 right and Model B got 26 right. How many percentage points more accurate is Model A?
10. 10.📦 Meera collected 110 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
11. 11.❌ Vihaan’s bird-song app was tested on 16 new bird songs and got 10 right. How many did it get wrong?
12. 12.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 24 right and Model B got 23 right. How many percentage points more accurate is Model A?
13. 13.📦 Kabir collected 150 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
14. 14.❌ Diya’s fruit sorter was tested on 49 new fruit photos and got 45 right. How many did it get wrong?
15. 15.🎯 Kabir’s recycling sorter was tested on 5 new waste photos and got 3 right. What is its accuracy in percent?
16. 16.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 17 right and Model B got 16 right. How many percentage points more accurate is Model A?
17. 17.🎯 Vihaan’s handwriting reader is 50% accurate. If it is tested on 20 new handwritten letters, how many should it get right?
18. 18.🧪 You can plan a simple AI project with… (a) a secret password (b) paper and examples (c) nothing at all (d) only a big robot
19. 19.🎯 Vihaan’s bird-song app was tested on 4 new bird songs and got 4 right. What is its accuracy in percent?
20. 20.📋 Planning an AI project: which comes first — label each example or split train and test? (a) label each example (b) split train and test
21. 21.📦 Arjun collected 40 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
22. 22.📦 Saanvi collected 100 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
23. 23.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to make it faster (c) to save paper (d) to see if it learned
24. 24.❌ Ishaan’s handwriting reader was tested on 44 new handwritten letters and got 43 right. How many did it get wrong?
25. 25.🎯 Saanvi’s spam spotter was tested on 5 new messages and got 5 right. What is its accuracy in percent?
26. 26.📋 Planning an AI project: which comes first — try unseen examples or correct bad labels? (a) try unseen examples (b) correct bad labels
27. 27.❌ Diya’s recycling sorter was tested on 40 new waste photos and got 36 right. How many did it get wrong?
28. 28.📋 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
29. 29.❌ Nisha’s recycling sorter was tested on 34 new waste photos and got 25 right. How many did it get wrong?
30. 30.📋 Planning an AI project: which comes first — improve data, retest or work out the accuracy? (a) improve data, retest (b) work out the accuracy
31. 31.📋 Planning an AI project: which comes first — test on new photos or let it learn patterns? (a) test on new photos (b) let it learn patterns
32. 32.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 31 right and Model B got 26 right. How many percentage points more accurate is Model A?
33. 33.📋 Planning an AI project: which comes first — let it learn patterns or fix it and test again? (a) let it learn patterns (b) fix it and test again
34. 34.📋 Planning an AI project: which comes first — train the model or fix it and test again? (a) train the model (b) fix it and test again
35. 35.📋 Planning an AI project: which comes first — gather many examples or work out the accuracy? (a) gather many examples (b) work out the accuracy
36. 36.⚖️ 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?
37. 37.📋 Planning an AI project: which comes first — work out the accuracy or pick a question to solve? (a) work out the accuracy (b) pick a question to solve
38. 38.❌ Saanvi’s fruit sorter was tested on 14 new fruit photos and got 13 right. How many did it get wrong?
39. 39.⚖️ 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?
40. 40.📦 Ananya collected 90 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?

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