Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 121 · 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.❌ Diya’s handwriting reader was tested on 33 new handwritten letters and got 24 right. How many did it get wrong?
2. 2.🎯 Nisha’s recycling sorter is 90% accurate. If it is tested on 90 new waste photos, how many should it get right?
3. 3.📋 Planning an AI project: which comes first — work out the accuracy or train the model? (a) work out the accuracy (b) train the model
4. 4.❌ Saanvi’s leaf identifier was tested on 29 new leaf photos and got 22 right. How many did it get wrong?
5. 5.📋 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
6. 6.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
7. 7.🎯 Tara’s leaf identifier was tested on 5 new leaf photos and got 3 right. What is its accuracy in percent?
8. 8.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to save paper (c) to make it bigger (d) to make it faster
9. 9.📋 Planning an AI project: which comes first — work out the accuracy or split train and test? (a) work out the accuracy (b) split train and test
10. 10.🎯 Nisha’s leaf identifier was tested on 50 new leaf photos and got 31 right. What is its accuracy in percent?
11. 11.📋 Planning an AI project: which comes first — label each example or recheck every label? (a) label each example (b) recheck every label
12. 12.📦 Rohan collected 60 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
13. 13.📋 Planning an AI project: which comes first — let it learn patterns or gather many examples? (a) let it learn patterns (b) gather many examples
14. 14.⚖️ Two leaf identifier models were tested on the same 25 leaf photos. Model A got 20 right and Model B got 18 right. How many percentage points more accurate is Model A?
15. 15.📋 Planning an AI project: which comes first — set aside test photos or train the model? (a) set aside test photos (b) train the model
16. 16.❌ Arjun’s bird-song app was tested on 50 new bird songs and got 41 right. How many did it get wrong?
17. 17.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 14 right and Model B got 10 right. How many percentage points more accurate is Model A?
18. 18.📋 Planning an AI project: which comes first — work out the accuracy or set aside test photos? (a) work out the accuracy (b) set aside test photos
19. 19.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 19 right and Model B got 13 right. How many percentage points more accurate is Model A?
20. 20.📋 Planning an AI project: which comes first — try unseen examples or choose what to sort? (a) try unseen examples (b) choose what to sort
21. 21.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 25 right and Model B got 22 right. How many percentage points more accurate is Model A?
22. 22.🎯 Meera’s spam spotter was tested on 5 new messages and got 5 right. What is its accuracy in percent?
23. 23.🧪 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
24. 24.🎯 Saanvi’s fruit sorter is 80% accurate. If it is tested on 70 new fruit photos, how many should it get right?
25. 25.⚖️ Two bird-song app models were tested on the same 25 bird songs. Model A got 25 right and Model B got 24 right. How many percentage points more accurate is Model A?
26. 26.📋 Planning an AI project: which comes first — calculate percent right or choose what to sort? (a) calculate percent right (b) choose what to sort
27. 27.📋 Planning an AI project: which comes first — work out the accuracy or recheck every label? (a) work out the accuracy (b) recheck every label
28. 28.❌ Tara’s recycling sorter was tested on 37 new waste photos and got 28 right. How many did it get wrong?
29. 29.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 8 right and Model B got 7 right. How many percentage points more accurate is Model A?
30. 30.🎯 Meera’s handwriting reader is 50% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
31. 31.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 8 right and Model B got 7 right. How many percentage points more accurate is Model A?
32. 32.📋 Planning an AI project: which comes first — tag each photo by type or recheck every label? (a) tag each photo by type (b) recheck every label
33. 33.🎯 Arjun’s handwriting reader is 60% accurate. If it is tested on 20 new handwritten letters, how many should it get right?
34. 34.🎯 Ishaan’s fruit sorter is 50% accurate. If it is tested on 100 new fruit photos, how many should it get right?
35. 35.📋 Planning an AI project: which comes first — choose what to sort or correct bad labels? (a) choose what to sort (b) correct bad labels
36. 36.❌ Kabir’s spam spotter was tested on 30 new messages and got 22 right. How many did it get wrong?
37. 37.📋 Planning an AI project: which comes first — test on new photos or split train and test? (a) test on new photos (b) split train and test
38. 38.❌ Meera’s handwriting reader was tested on 28 new handwritten letters and got 26 right. How many did it get wrong?
39. 39.❌ Nisha’s recycling sorter was tested on 26 new waste photos and got 20 right. How many did it get wrong?
40. 40.📦 Diya collected 70 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?

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