Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 270 · 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.🧪 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 faster (d) to make it bigger
2. 2.🎯 Rohan’s leaf identifier is 80% accurate. If it is tested on 100 new leaf photos, how many should it get right?
3. 3.📋 Planning an AI project: which comes first — improve data, retest or test on new photos? (a) improve data, retest (b) test on new photos
4. 4.🎯 Kabir’s spam spotter is 50% accurate. If it is tested on 70 new messages, how many should it get right?
5. 5.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 9 right and Model B got 6 right. How many percentage points more accurate is Model A?
6. 6.🎯 Rohan’s fruit sorter was tested on 20 new fruit photos and got 19 right. What is its accuracy in percent?
7. 7.📋 Planning an AI project: which comes first — fix it and test again or try unseen examples? (a) fix it and test again (b) try unseen examples
8. 8.📦 Rohan collected 70 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
9. 9.📋 Planning an AI project: which comes first — test on new photos or gather many examples? (a) test on new photos (b) gather many examples
10. 10.📋 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
11. 11.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 7 right and Model B got 6 right. How many percentage points more accurate is Model A?
12. 12.🧪 What is accuracy? (a) correct + total (b) total × 2 (c) correct ÷ total × 100 (d) total − correct
13. 13.📋 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
14. 14.🎯 Rohan’s fruit sorter was tested on 25 new fruit photos and got 14 right. What is its accuracy in percent?
15. 15.📦 Tara collected 60 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
16. 16.🎯 Arjun’s bird-song app is 80% accurate. If it is tested on 50 new bird songs, how many should it get right?
17. 17.📦 Nisha collected 80 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
18. 18.📋 Planning an AI project: which comes first — train the model or set aside test photos? (a) train the model (b) set aside test photos
19. 19.📋 Planning an AI project: which comes first — label each example or collect fruit photos? (a) label each example (b) collect fruit photos
20. 20.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) a new colour screen (c) more labelled examples (d) a louder speaker
21. 21.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 9 right and Model B got 8 right. How many percentage points more accurate is Model A?
22. 22.🎯 Rohan’s fruit sorter was tested on 10 new fruit photos and got 5 right. What is its accuracy in percent?
23. 23.🧪 You can plan a simple AI project with… (a) nothing at all (b) only a big robot (c) a secret password (d) paper and examples
24. 24.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 50 right and Model B got 48 right. How many percentage points more accurate is Model A?
25. 25.📦 Nisha collected 70 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
26. 26.🎯 Kabir’s fruit sorter is 90% accurate. If it is tested on 90 new fruit photos, how many should it get right?
27. 27.❌ Rohan’s spam spotter was tested on 33 new messages and got 29 right. How many did it get wrong?
28. 28.📋 Planning an AI project: which comes first — set aside test photos or label each example? (a) set aside test photos (b) label each example
29. 29.🎯 Ananya’s recycling sorter is 90% accurate. If it is tested on 70 new waste photos, how many should it get right?
30. 30.📋 Planning an AI project: which comes first — gather many examples or correct bad labels? (a) gather many examples (b) correct bad labels
31. 31.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 43 right and Model B got 38 right. How many percentage points more accurate is Model A?
32. 32.📋 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
33. 33.🎯 Ishaan’s recycling sorter is 50% accurate. If it is tested on 20 new waste photos, how many should it get right?
34. 34.⚖️ Two leaf identifier models were tested on the same 20 leaf photos. Model A got 20 right and Model B got 19 right. How many percentage points more accurate is Model A?
35. 35.📋 Planning an AI project: which comes first — recheck every label or train the model? (a) recheck every label (b) train the model
36. 36.🎯 Vihaan’s recycling sorter is 70% accurate. If it is tested on 40 new waste photos, how many should it get right?
37. 37.📋 Planning an AI project: which comes first — work out the accuracy or tag each photo by type? (a) work out the accuracy (b) tag each photo by type
38. 38.📋 Planning an AI project: which comes first — collect fruit photos or fix it and test again? (a) collect fruit photos (b) fix it and test again
39. 39.❌ Ananya’s spam spotter was tested on 40 new messages and got 38 right. How many did it get wrong?
40. 40.❌ Aarav’s leaf identifier was tested on 40 new leaf photos and got 32 right. How many did it get wrong?

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