Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 786 · 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.🎯 Meera’s bird-song app was tested on 20 new bird songs and got 18 right. What is its accuracy in percent?
2. 2.📋 Planning an AI project: which comes first — fix it and test again or let it learn patterns? (a) fix it and test again (b) let it learn patterns
3. 3.❌ Vihaan’s leaf identifier was tested on 17 new leaf photos and got 11 right. How many did it get wrong?
4. 4.🎯 Kabir’s bird-song app was tested on 50 new bird songs and got 31 right. What is its accuracy in percent?
5. 5.⚖️ 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?
6. 6.🎯 Kabir’s handwriting reader is 50% accurate. If it is tested on 100 new handwritten letters, how many should it get right?
7. 7.❌ Vihaan’s fruit sorter was tested on 30 new fruit photos and got 23 right. How many did it get wrong?
8. 8.📋 Planning an AI project: which comes first — collect fruit photos or pick a question to solve? (a) collect fruit photos (b) pick a question to solve
9. 9.📋 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
10. 10.📋 Planning an AI project: which comes first — train the model or correct bad labels? (a) train the model (b) correct bad labels
11. 11.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) more labelled examples (c) fewer examples (d) a new colour screen
12. 12.📋 Planning an AI project: which comes first — test on new photos or fix it and test again? (a) test on new photos (b) fix it and test again
13. 13.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 48 right and Model B got 46 right. How many percentage points more accurate is Model A?
14. 14.🎯 Ishaan’s handwriting reader was tested on 50 new handwritten letters and got 29 right. What is its accuracy in percent?
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.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to save paper (c) to see if it learned (d) to make it faster
17. 17.❌ Rohan’s leaf identifier was tested on 42 new leaf photos and got 40 right. How many did it get wrong?
18. 18.📦 Kabir collected 100 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
19. 19.🧪 You can plan a simple AI project with… (a) paper and examples (b) only a big robot (c) nothing at all (d) a secret password
20. 20.📋 Planning an AI project: which comes first — test on new photos or label each example? (a) test on new photos (b) label each example
21. 21.📦 Saanvi collected 200 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
22. 22.🎯 Meera’s leaf identifier was tested on 20 new leaf photos and got 10 right. What is its accuracy in percent?
23. 23.📋 Planning an AI project: which comes first — improve data, retest or split train and test? (a) improve data, retest (b) split train and test
24. 24.📋 Planning an AI project: which comes first — label each example or pick a question to solve? (a) label each example (b) pick a question to solve
25. 25.🎯 Rohan’s leaf identifier is 50% accurate. If it is tested on 60 new leaf photos, how many should it get right?
26. 26.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct + total (d) correct ÷ total × 100
27. 27.📋 Planning an AI project: which comes first — collect fruit photos or let it learn patterns? (a) collect fruit photos (b) let it learn patterns
28. 28.🎯 Kabir’s fruit sorter is 60% accurate. If it is tested on 40 new fruit photos, how many should it get right?
29. 29.❌ Aarav’s leaf identifier was tested on 33 new leaf photos and got 26 right. How many did it get wrong?
30. 30.📦 Arjun collected 180 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 — fix it and test again or calculate percent right? (a) fix it and test again (b) calculate percent right
32. 32.📋 Planning an AI project: which comes first — fix it and test again or train the model? (a) fix it and test again (b) train the model
33. 33.❌ Nisha’s leaf identifier was tested on 19 new leaf photos and got 11 right. How many did it get wrong?
34. 34.🎯 Ishaan’s spam spotter was tested on 10 new messages and got 6 right. What is its accuracy in percent?
35. 35.📋 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
36. 36.🎯 Ananya’s leaf identifier was tested on 20 new leaf photos and got 11 right. What is its accuracy in percent?
37. 37.🎯 Meera’s handwriting reader was tested on 10 new handwritten letters and got 10 right. What is its accuracy in percent?
38. 38.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
39. 39.❌ Vihaan’s handwriting reader was tested on 47 new handwritten letters and got 46 right. How many did it get wrong?
40. 40.🎯 Rohan’s fruit sorter was tested on 50 new fruit photos and got 32 right. What is its accuracy in percent?

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