Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 774 · 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.📦 Ananya collected 140 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
2. 2.🎯 Meera’s bird-song app was tested on 5 new bird songs and got 3 right. What is its accuracy in percent?
3. 3.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to make it faster (c) to save paper (d) to make it bigger
4. 4.📦 Ananya collected 70 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
5. 5.🧪 What is accuracy? (a) total − correct (b) correct ÷ total × 100 (c) total × 2 (d) correct + total
6. 6.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) fewer examples (c) a new colour screen (d) more labelled examples
7. 7.📋 Planning an AI project: which comes first — correct bad labels or fix it and test again? (a) correct bad labels (b) fix it and test again
8. 8.📦 Nisha collected 120 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
9. 9.❌ Nisha’s fruit sorter was tested on 18 new fruit photos and got 16 right. How many did it get wrong?
10. 10.📋 Planning an AI project: which comes first — calculate percent right or try unseen examples? (a) calculate percent right (b) try unseen examples
11. 11.📋 Planning an AI project: which comes first — work out the accuracy or set aside test photos? (a) work out the accuracy (b) set aside test photos
12. 12.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
13. 13.📋 Planning an AI project: which comes first — split train and test or pick a question to solve? (a) split train and test (b) pick a question to solve
14. 14.🎯 Ananya’s bird-song app was tested on 25 new bird songs and got 25 right. What is its accuracy in percent?
15. 15.🎯 Aarav’s leaf identifier was tested on 50 new leaf photos and got 30 right. What is its accuracy in percent?
16. 16.❌ Meera’s fruit sorter was tested on 43 new fruit photos and got 36 right. How many did it get wrong?
17. 17.📋 Planning an AI project: which comes first — tag each photo by type or gather many examples? (a) tag each photo by type (b) gather many examples
18. 18.🎯 Kabir’s fruit sorter is 60% accurate. If it is tested on 30 new fruit photos, how many should it get right?
19. 19.⚖️ 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?
20. 20.🎯 Meera’s bird-song app is 80% accurate. If it is tested on 50 new bird songs, how many should it get right?
21. 21.📦 Rohan collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
22. 22.❌ Arjun’s fruit sorter was tested on 21 new fruit photos and got 16 right. How many did it get wrong?
23. 23.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 10 right and Model B got 8 right. How many percentage points more accurate is Model A?
24. 24.📋 Planning an AI project: which comes first — label each example or collect fruit photos? (a) label each example (b) collect fruit photos
25. 25.📦 Ananya collected 150 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
26. 26.🎯 Saanvi’s fruit sorter was tested on 25 new fruit photos and got 22 right. What is its accuracy in percent?
27. 27.🧪 You can plan a simple AI project with… (a) a secret password (b) only a big robot (c) paper and examples (d) nothing at all
28. 28.🎯 Diya’s spam spotter is 50% accurate. If it is tested on 50 new messages, how many should it get right?
29. 29.❌ Ishaan’s fruit sorter was tested on 29 new fruit photos and got 22 right. How many did it get wrong?
30. 30.🎯 Aarav’s bird-song app was tested on 25 new bird songs and got 20 right. What is its accuracy in percent?
31. 31.📋 Planning an AI project: which comes first — tag each photo by type or pick a question to solve? (a) tag each photo by type (b) pick a question to solve
32. 32.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 5 right. How many percentage points more accurate is Model A?
33. 33.🎯 Meera’s leaf identifier is 60% accurate. If it is tested on 80 new leaf photos, how many should it get right?
34. 34.📋 Planning an AI project: which comes first — train the model or try unseen examples? (a) train the model (b) try unseen examples
35. 35.📋 Planning an AI project: which comes first — improve data, retest or pick a question to solve? (a) improve data, retest (b) pick a question to solve
36. 36.📦 Aarav collected 130 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
37. 37.📋 Planning an AI project: which comes first — test on new photos or work out the accuracy? (a) test on new photos (b) work out the accuracy
38. 38.📋 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
39. 39.⚖️ Two spam spotter models were tested on the same 20 messages. Model A got 19 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 — tag each photo by type or work out the accuracy? (a) tag each photo by type (b) work out the accuracy

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