Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 29 · 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.🧪 What is accuracy? (a) correct ÷ total × 100 (b) total × 2 (c) total − correct (d) correct + total
2. 2.📋 Planning an AI project: which comes first — calculate percent right or let it learn patterns? (a) calculate percent right (b) let it learn patterns
3. 3.📋 Planning an AI project: which comes first — test on new photos or let it learn patterns? (a) test on new photos (b) let it learn patterns
4. 4.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 19 right and Model B got 10 right. How many percentage points more accurate is Model A?
5. 5.📦 Nisha collected 170 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
6. 6.📋 Planning an AI project: which comes first — recheck every label or calculate percent right? (a) recheck every label (b) calculate percent right
7. 7.🎯 Saanvi’s bird-song app is 60% accurate. If it is tested on 30 new bird songs, how many should it get right?
8. 8.🎯 Tara’s leaf identifier was tested on 20 new leaf photos and got 12 right. What is its accuracy in percent?
9. 9.📦 Rohan collected 140 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
10. 10.🧪 You can plan a simple AI project with… (a) a secret password (b) paper and examples (c) only a big robot (d) nothing at all
11. 11.❌ Aarav’s leaf identifier was tested on 34 new leaf photos and got 28 right. How many did it get wrong?
12. 12.🎯 Kabir’s leaf identifier was tested on 10 new leaf photos and got 7 right. What is its accuracy in percent?
13. 13.📦 Ananya collected 90 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
14. 14.🎯 Rohan’s recycling sorter was tested on 4 new waste photos and got 3 right. What is its accuracy in percent?
15. 15.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 8 right. How many percentage points more accurate is Model A?
16. 16.🎯 Tara’s leaf identifier is 90% accurate. If it is tested on 20 new leaf photos, how many should it get right?
17. 17.📦 Ishaan collected 110 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
18. 18.📋 Planning an AI project: which comes first — improve data, retest or work out the accuracy? (a) improve data, retest (b) work out the accuracy
19. 19.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) fewer examples (c) a new colour screen (d) a louder speaker
20. 20.🎯 Kabir’s spam spotter is 90% accurate. If it is tested on 60 new messages, how many should it get right?
21. 21.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 7 right and Model B got 5 right. How many percentage points more accurate is Model A?
22. 22.🎯 Nisha’s handwriting reader was tested on 25 new handwritten letters and got 24 right. What is its accuracy in percent?
23. 23.🎯 Rohan’s recycling sorter is 50% accurate. If it is tested on 50 new waste photos, how many should it get right?
24. 24.🎯 Aarav’s bird-song app is 50% accurate. If it is tested on 80 new bird songs, how many should it get right?
25. 25.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it faster (c) to make it bigger (d) to see if it learned
26. 26.📋 Planning an AI project: which comes first — improve data, retest or try unseen examples? (a) improve data, retest (b) try unseen examples
27. 27.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 8 right and Model B got 5 right. How many percentage points more accurate is Model A?
28. 28.📋 Planning an AI project: which comes first — fix it and test again or calculate percent right? (a) fix it and test again (b) calculate percent right
29. 29.📋 Planning an AI project: which comes first — let it learn patterns or correct bad labels? (a) let it learn patterns (b) correct bad labels
30. 30.🎯 Ishaan’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
31. 31.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 23 right and Model B got 19 right. How many percentage points more accurate is Model A?
32. 32.🎯 Kabir’s bird-song app was tested on 25 new bird songs and got 22 right. What is its accuracy in percent?
33. 33.📋 Planning an AI project: which comes first — train the model or calculate percent right? (a) train the model (b) calculate percent right
34. 34.🎯 Diya’s leaf identifier was tested on 10 new leaf photos and got 6 right. What is its accuracy in percent?
35. 35.📋 Planning an AI project: which comes first — let it learn patterns or try unseen examples? (a) let it learn patterns (b) try unseen examples
36. 36.📋 Planning an AI project: which comes first — correct bad labels or label each example? (a) correct bad labels (b) label each example
37. 37.📦 Rohan collected 50 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
38. 38.🎯 Saanvi’s leaf identifier was tested on 10 new leaf photos and got 5 right. What is its accuracy in percent?
39. 39.🎯 Meera’s leaf identifier is 70% accurate. If it is tested on 10 new leaf photos, how many should it get right?
40. 40.🎯 Rohan’s leaf identifier is 70% accurate. If it is tested on 30 new leaf photos, how many should it get right?

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