Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 855 · 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 — improve data, retest or tag each photo by type? (a) improve data, retest (b) tag each photo by type
2. 2.📦 Nisha collected 190 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
3. 3.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 24 right and Model B got 16 right. How many percentage points more accurate is Model A?
4. 4.📋 Planning an AI project: which comes first — train the model or try unseen examples? (a) train the model (b) try unseen examples
5. 5.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to make it faster (c) to save paper (d) to see if it learned
6. 6.❌ Kabir’s bird-song app was tested on 32 new bird songs and got 24 right. How many did it get wrong?
7. 7.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 8 right and Model B got 7 right. How many percentage points more accurate is Model A?
8. 8.🧪 You can plan a simple AI project with… (a) nothing at all (b) paper and examples (c) a secret password (d) only a big robot
9. 9.📋 Planning an AI project: which comes first — label each example or try unseen examples? (a) label each example (b) try unseen examples
10. 10.🎯 Ishaan’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
11. 11.⚖️ 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?
12. 12.📋 Planning an AI project: which comes first — improve data, retest or label each example? (a) improve data, retest (b) label each example
13. 13.❌ Nisha’s spam spotter was tested on 39 new messages and got 38 right. How many did it get wrong?
14. 14.📋 Planning an AI project: which comes first — recheck every label or try unseen examples? (a) recheck every label (b) try unseen examples
15. 15.🎯 Ishaan’s bird-song app was tested on 25 new bird songs and got 16 right. What is its accuracy in percent?
16. 16.🎯 Kabir’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
17. 17.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 19 right and Model B got 18 right. How many percentage points more accurate is Model A?
18. 18.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct ÷ total × 100 (d) correct + total
19. 19.🎯 Saanvi’s handwriting reader is 90% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
20. 20.❌ Arjun’s recycling sorter was tested on 45 new waste photos and got 37 right. How many did it get wrong?
21. 21.❌ Nisha’s spam spotter was tested on 31 new messages and got 24 right. How many did it get wrong?
22. 22.📋 Planning an AI project: which comes first — collect fruit photos or tag each photo by type? (a) collect fruit photos (b) tag each photo by type
23. 23.❌ Nisha’s fruit sorter was tested on 15 new fruit photos and got 12 right. How many did it get wrong?
24. 24.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 20 right and Model B got 15 right. How many percentage points more accurate is Model A?
25. 25.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 7 right and Model B got 6 right. How many percentage points more accurate is Model A?
26. 26.📋 Planning an AI project: which comes first — collect fruit photos or improve data, retest? (a) collect fruit photos (b) improve data, retest
27. 27.📋 Planning an AI project: which comes first — label each example or collect fruit photos? (a) label each example (b) collect fruit photos
28. 28.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) a louder speaker (c) more labelled examples (d) a new colour screen
29. 29.📋 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
30. 30.📋 Planning an AI project: which comes first — pick a question to solve or split train and test? (a) pick a question to solve (b) split train and test
31. 31.❌ Diya’s fruit sorter was tested on 48 new fruit photos and got 46 right. How many did it get wrong?
32. 32.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
33. 33.🎯 Aarav’s spam spotter was tested on 5 new messages and got 4 right. What is its accuracy in percent?
34. 34.📋 Planning an AI project: which comes first — try unseen examples or let it learn patterns? (a) try unseen examples (b) let it learn patterns
35. 35.📋 Planning an AI project: which comes first — test on new photos or set aside test photos? (a) test on new photos (b) set aside test photos
36. 36.📋 Planning an AI project: which comes first — pick a question to solve or let it learn patterns? (a) pick a question to solve (b) let it learn patterns
37. 37.🎯 Vihaan’s leaf identifier is 90% accurate. If it is tested on 30 new leaf photos, how many should it get right?
38. 38.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 8 right and Model B got 7 right. How many percentage points more accurate is Model A?
39. 39.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 17 right and Model B got 13 right. How many percentage points more accurate is Model A?
40. 40.🎯 Arjun’s leaf identifier was tested on 50 new leaf photos and got 42 right. What is its accuracy in percent?

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