Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 750 · 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.🎯 Saanvi’s recycling sorter was tested on 4 new waste photos and got 2 right. What is its accuracy in percent?
2. 2.📋 Planning an AI project: which comes first — correct bad labels or tag each photo by type? (a) correct bad labels (b) tag each photo by type
3. 3.🎯 Tara’s leaf identifier was tested on 10 new leaf photos and got 10 right. What is its accuracy in percent?
4. 4.📋 Planning an AI project: which comes first — work out the accuracy or correct bad labels? (a) work out the accuracy (b) correct bad labels
5. 5.📋 Planning an AI project: which comes first — recheck every label or set aside test photos? (a) recheck every label (b) set aside test photos
6. 6.📦 Saanvi collected 120 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
7. 7.📋 Planning an AI project: which comes first — gather many examples or label each example? (a) gather many examples (b) label each example
8. 8.🎯 Diya’s recycling sorter was tested on 50 new waste photos and got 42 right. What is its accuracy in percent?
9. 9.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it faster (c) to see if it learned (d) to make it bigger
10. 10.🧪 What is accuracy? (a) correct ÷ total × 100 (b) correct + total (c) total − correct (d) total × 2
11. 11.🎯 Aarav’s leaf identifier is 90% accurate. If it is tested on 60 new leaf photos, how many should it get right?
12. 12.🎯 Ishaan’s spam spotter is 50% accurate. If it is tested on 40 new messages, how many should it get right?
13. 13.📋 Planning an AI project: which comes first — train the model or improve data, retest? (a) train the model (b) improve data, retest
14. 14.❌ Vihaan’s spam spotter was tested on 33 new messages and got 26 right. How many did it get wrong?
15. 15.🧪 You can plan a simple AI project with… (a) paper and examples (b) nothing at all (c) only a big robot (d) a secret password
16. 16.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 19 right and Model B got 16 right. How many percentage points more accurate is Model A?
17. 17.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) fewer examples (c) more labelled examples (d) a new colour screen
18. 18.📋 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
19. 19.🎯 Arjun’s spam spotter was tested on 10 new messages and got 6 right. What is its accuracy in percent?
20. 20.📋 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
21. 21.📋 Planning an AI project: which comes first — recheck every label or tag each photo by type? (a) recheck every label (b) tag each photo by type
22. 22.🎯 Rohan’s bird-song app is 60% accurate. If it is tested on 20 new bird songs, how many should it get right?
23. 23.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 25 right and Model B got 24 right. How many percentage points more accurate is Model A?
24. 24.🎯 Meera’s recycling sorter is 70% accurate. If it is tested on 50 new waste photos, how many should it get right?
25. 25.📋 Planning an AI project: which comes first — calculate percent right or test on new photos? (a) calculate percent right (b) test on new photos
26. 26.❌ Diya’s fruit sorter was tested on 15 new fruit photos and got 12 right. How many did it get wrong?
27. 27.📋 Planning an AI project: which comes first — try unseen examples or calculate percent right? (a) try unseen examples (b) calculate percent right
28. 28.❌ Saanvi’s recycling sorter was tested on 18 new waste photos and got 12 right. How many did it get wrong?
29. 29.📋 Planning an AI project: which comes first — gather many examples or improve data, retest? (a) gather many examples (b) improve data, retest
30. 30.📦 Tara collected 120 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
31. 31.📦 Vihaan collected 160 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
32. 32.🎯 Ananya’s fruit sorter was tested on 5 new fruit photos and got 5 right. What is its accuracy in percent?
33. 33.📋 Planning an AI project: which comes first — let it learn patterns or try unseen examples? (a) let it learn patterns (b) try unseen examples
34. 34.📋 Planning an AI project: which comes first — work out the accuracy or test on new photos? (a) work out the accuracy (b) test on new photos
35. 35.📦 Arjun collected 100 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
36. 36.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 44 right and Model B got 36 right. How many percentage points more accurate is Model A?
37. 37.📋 Planning an AI project: which comes first — gather many examples or tag each photo by type? (a) gather many examples (b) tag each photo by type
38. 38.❌ Ishaan’s spam spotter was tested on 15 new messages and got 11 right. How many did it get wrong?
39. 39.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 16 right and Model B got 13 right. How many percentage points more accurate is Model A?
40. 40.📋 Planning an AI project: which comes first — correct bad labels or label each example? (a) correct bad labels (b) label each example

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