Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 566 · 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.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 30 right and Model B got 29 right. How many percentage points more accurate is Model A?
2. 2.⚖️ Two spam spotter models were tested on the same 20 messages. Model A got 12 right and Model B got 10 right. How many percentage points more accurate is Model A?
3. 3.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to make it faster (c) to see if it learned (d) to save paper
4. 4.📋 Planning an AI project: which comes first — split train and test or work out the accuracy? (a) split train and test (b) work out the accuracy
5. 5.📋 Planning an AI project: which comes first — collect fruit photos or set aside test photos? (a) collect fruit photos (b) set aside test photos
6. 6.🧪 What is accuracy? (a) correct ÷ total × 100 (b) total − correct (c) correct + total (d) total × 2
7. 7.🧪 You can plan a simple AI project with… (a) only a big robot (b) nothing at all (c) paper and examples (d) a secret password
8. 8.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) fewer examples (c) a louder speaker (d) a new colour screen
9. 9.🎯 Vihaan’s spam spotter is 60% accurate. If it is tested on 50 new messages, how many should it get right?
10. 10.📋 Planning an AI project: which comes first — correct bad labels or test on new photos? (a) correct bad labels (b) test on new photos
11. 11.🎯 Aarav’s spam spotter was tested on 10 new messages and got 9 right. What is its accuracy in percent?
12. 12.📋 Planning an AI project: which comes first — let it learn patterns or test on new photos? (a) let it learn patterns (b) test on new photos
13. 13.❌ Saanvi’s spam spotter was tested on 41 new messages and got 37 right. How many did it get wrong?
14. 14.📋 Planning an AI project: which comes first — try unseen examples or set aside test photos? (a) try unseen examples (b) set aside test photos
15. 15.❌ Rohan’s leaf identifier was tested on 29 new leaf photos and got 25 right. How many did it get wrong?
16. 16.📋 Planning an AI project: which comes first — gather many examples or correct bad labels? (a) gather many examples (b) correct bad labels
17. 17.📋 Planning an AI project: which comes first — improve data, retest or split train and test? (a) improve data, retest (b) split train and test
18. 18.📋 Planning an AI project: which comes first — set aside test photos or label each example? (a) set aside test photos (b) label each example
19. 19.🎯 Nisha’s recycling sorter was tested on 20 new waste photos and got 12 right. What is its accuracy in percent?
20. 20.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 10 right and Model B got 5 right. How many percentage points more accurate is Model A?
21. 21.📦 Aarav collected 50 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
22. 22.📋 Planning an AI project: which comes first — split train and test or tag each photo by type? (a) split train and test (b) tag each photo by type
23. 23.📦 Kabir collected 70 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
24. 24.📋 Planning an AI project: which comes first — set aside test photos or improve data, retest? (a) set aside test photos (b) improve data, retest
25. 25.📋 Planning an AI project: which comes first — gather many examples or label each example? (a) gather many examples (b) label each example
26. 26.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 25 right and Model B got 21 right. How many percentage points more accurate is Model A?
27. 27.📦 Diya collected 190 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
28. 28.📦 Ananya collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
29. 29.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 14 right and Model B got 13 right. How many percentage points more accurate is Model A?
30. 30.🎯 Vihaan’s leaf identifier was tested on 5 new leaf photos and got 4 right. What is its accuracy in percent?
31. 31.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 47 right and Model B got 38 right. How many percentage points more accurate is Model A?
32. 32.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 37 right and Model B got 31 right. How many percentage points more accurate is Model A?
33. 33.🎯 Meera’s fruit sorter was tested on 5 new fruit photos and got 3 right. What is its accuracy in percent?
34. 34.❌ Rohan’s leaf identifier was tested on 30 new leaf photos and got 26 right. How many did it get wrong?
35. 35.🎯 Aarav’s fruit sorter is 80% accurate. If it is tested on 40 new fruit photos, how many should it get right?
36. 36.🎯 Rohan’s spam spotter is 70% accurate. If it is tested on 60 new messages, how many should it get right?
37. 37.⚖️ Two fruit sorter models were tested on the same 50 fruit photos. Model A got 37 right and Model B got 30 right. How many percentage points more accurate is Model A?
38. 38.📋 Planning an AI project: which comes first — choose what to sort or correct bad labels? (a) choose what to sort (b) correct bad labels
39. 39.❌ Rohan’s fruit sorter was tested on 20 new fruit photos and got 19 right. How many did it get wrong?
40. 40.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 50 right and Model B got 34 right. How many percentage points more accurate is Model A?

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