Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 758 · 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.🧪 What is accuracy? (a) correct ÷ total × 100 (b) correct + total (c) total × 2 (d) total − correct
2. 2.🎯 Saanvi’s recycling sorter was tested on 5 new waste photos and got 5 right. What is its accuracy in percent?
3. 3.🎯 Kabir’s spam spotter is 50% accurate. If it is tested on 60 new messages, how many should it get right?
4. 4.🧪 You can plan a simple AI project with… (a) only a big robot (b) nothing at all (c) a secret password (d) paper and examples
5. 5.❌ Rohan’s handwriting reader was tested on 30 new handwritten letters and got 25 right. How many did it get wrong?
6. 6.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) a louder speaker (c) a new colour screen (d) more labelled examples
7. 7.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 8 right and Model B got 5 right. How many percentage points more accurate is Model A?
8. 8.📋 Planning an AI project: which comes first — correct bad labels or calculate percent right? (a) correct bad labels (b) calculate percent right
9. 9.📋 Planning an AI project: which comes first — improve data, retest or split train and test? (a) improve data, retest (b) split train and test
10. 10.📋 Planning an AI project: which comes first — fix it and test again or test on new photos? (a) fix it and test again (b) test on new photos
11. 11.📋 Planning an AI project: which comes first — train the model or work out the accuracy? (a) train the model (b) work out the accuracy
12. 12.📦 Nisha collected 140 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
13. 13.🎯 Ananya’s handwriting reader was tested on 50 new handwritten letters and got 35 right. What is its accuracy in percent?
14. 14.⚖️ Two leaf identifier models were tested on the same 25 leaf photos. Model A got 18 right and Model B got 16 right. How many percentage points more accurate is Model A?
15. 15.📋 Planning an AI project: which comes first — tag each photo by type or fix it and test again? (a) tag each photo by type (b) fix it and test again
16. 16.🎯 Nisha’s fruit sorter is 50% accurate. If it is tested on 30 new fruit photos, how many should it get right?
17. 17.📦 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?
18. 18.🎯 Vihaan’s bird-song app is 50% accurate. If it is tested on 20 new bird songs, how many should it get right?
19. 19.📋 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
20. 20.❌ Arjun’s fruit sorter was tested on 24 new fruit photos and got 16 right. How many did it get wrong?
21. 21.🎯 Arjun’s recycling sorter was tested on 10 new waste photos and got 8 right. What is its accuracy in percent?
22. 22.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to make it bigger (c) to see if it learned (d) to save paper
23. 23.📋 Planning an AI project: which comes first — gather many examples or fix it and test again? (a) gather many examples (b) fix it and test again
24. 24.📋 Planning an AI project: which comes first — correct bad labels or improve data, retest? (a) correct bad labels (b) improve data, retest
25. 25.🎯 Rohan’s leaf identifier was tested on 50 new leaf photos and got 32 right. What is its accuracy in percent?
26. 26.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 19 right and Model B got 18 right. How many percentage points more accurate is Model A?
27. 27.🎯 Diya’s handwriting reader was tested on 20 new handwritten letters and got 10 right. What is its accuracy in percent?
28. 28.🎯 Arjun’s fruit sorter is 50% accurate. If it is tested on 30 new fruit photos, how many should it get right?
29. 29.❌ Diya’s spam spotter was tested on 20 new messages and got 17 right. How many did it get wrong?
30. 30.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
31. 31.⚖️ Two spam spotter models were tested on the same 20 messages. Model A got 20 right and Model B got 17 right. How many percentage points more accurate is Model A?
32. 32.❌ Diya’s leaf identifier was tested on 48 new leaf photos and got 41 right. How many did it get wrong?
33. 33.❌ Diya’s handwriting reader was tested on 25 new handwritten letters and got 20 right. How many did it get wrong?
34. 34.🎯 Meera’s leaf identifier was tested on 5 new leaf photos and got 3 right. What is its accuracy in percent?
35. 35.🎯 Rohan’s recycling sorter was tested on 20 new waste photos and got 14 right. What is its accuracy in percent?
36. 36.📋 Planning an AI project: which comes first — calculate percent right or test on new photos? (a) calculate percent right (b) test on new photos
37. 37.🎯 Saanvi’s leaf identifier was tested on 5 new leaf photos and got 4 right. What is its accuracy in percent?
38. 38.📋 Planning an AI project: which comes first — try unseen examples or train the model? (a) try unseen examples (b) train the model
39. 39.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 20 right and Model B got 14 right. How many percentage points more accurate is Model A?
40. 40.📋 Planning an AI project: which comes first — correct bad labels or try unseen examples? (a) correct bad labels (b) try unseen examples

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