Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 831 · 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 — label each example or split train and test? (a) label each example (b) split train and test
2. 2.📦 Nisha collected 200 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
3. 3.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to see if it learned (c) to make it faster (d) to make it bigger
4. 4.📦 Vihaan collected 130 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
5. 5.🎯 Saanvi’s bird-song app was tested on 10 new bird songs and got 9 right. What is its accuracy in percent?
6. 6.🧪 You can plan a simple AI project with… (a) paper and examples (b) only a big robot (c) a secret password (d) nothing at all
7. 7.❌ Saanvi’s bird-song app was tested on 32 new bird songs and got 25 right. How many did it get wrong?
8. 8.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 47 right and Model B got 42 right. How many percentage points more accurate is Model A?
9. 9.🎯 Nisha’s recycling sorter is 50% accurate. If it is tested on 90 new waste photos, how many should it get right?
10. 10.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) a new colour screen (c) fewer examples (d) more labelled examples
11. 11.📦 Saanvi collected 100 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
12. 12.📋 Planning an AI project: which comes first — tag each photo by type or split train and test? (a) tag each photo by type (b) split train and test
13. 13.📋 Planning an AI project: which comes first — choose what to sort or train the model? (a) choose what to sort (b) train the model
14. 14.📋 Planning an AI project: which comes first — pick a question to solve or correct bad labels? (a) pick a question to solve (b) correct bad labels
15. 15.📋 Planning an AI project: which comes first — fix it and test again or collect fruit photos? (a) fix it and test again (b) collect fruit photos
16. 16.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 7 right and Model B got 6 right. How many percentage points more accurate is Model A?
17. 17.🎯 Saanvi’s recycling sorter is 80% accurate. If it is tested on 80 new waste photos, how many should it get right?
18. 18.🎯 Diya’s handwriting reader was tested on 25 new handwritten letters and got 19 right. What is its accuracy in percent?
19. 19.📋 Planning an AI project: which comes first — split train and test or choose what to sort? (a) split train and test (b) choose what to sort
20. 20.📋 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
21. 21.🎯 Arjun’s leaf identifier is 80% accurate. If it is tested on 60 new leaf photos, how many should it get right?
22. 22.🎯 Diya’s recycling sorter is 90% accurate. If it is tested on 100 new waste photos, how many should it get right?
23. 23.🎯 Saanvi’s spam spotter was tested on 4 new messages and got 2 right. What is its accuracy in percent?
24. 24.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 8 right and Model B got 6 right. How many percentage points more accurate is Model A?
25. 25.📋 Planning an AI project: which comes first — fix it and test again or tag each photo by type? (a) fix it and test again (b) tag each photo by type
26. 26.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 18 right and Model B got 10 right. How many percentage points more accurate is Model A?
27. 27.📋 Planning an AI project: which comes first — gather many examples or label each example? (a) gather many examples (b) label each example
28. 28.📋 Planning an AI project: which comes first — improve data, retest or recheck every label? (a) improve data, retest (b) recheck every label
29. 29.📋 Planning an AI project: which comes first — let it learn patterns or collect fruit photos? (a) let it learn patterns (b) collect fruit photos
30. 30.🎯 Aarav’s handwriting reader was tested on 20 new handwritten letters and got 20 right. What is its accuracy in percent?
31. 31.🧪 What is accuracy? (a) total − correct (b) correct ÷ total × 100 (c) total × 2 (d) correct + total
32. 32.❌ Nisha’s leaf identifier was tested on 41 new leaf photos and got 36 right. How many did it get wrong?
33. 33.❌ Ishaan’s recycling sorter was tested on 34 new waste photos and got 25 right. How many did it get wrong?
34. 34.🎯 Kabir’s leaf identifier is 70% accurate. If it is tested on 90 new leaf photos, how many should it get right?
35. 35.📋 Planning an AI project: which comes first — collect fruit photos or let it learn patterns? (a) collect fruit photos (b) let it learn patterns
36. 36.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 25 right and Model B got 22 right. How many percentage points more accurate is Model A?
37. 37.📋 Planning an AI project: which comes first — improve data, retest or pick a question to solve? (a) improve data, retest (b) pick a question to solve
38. 38.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
39. 39.📦 Kabir collected 160 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
40. 40.❌ Vihaan’s recycling sorter was tested on 16 new waste photos and got 10 right. How many did it get wrong?

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