Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 31 · 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 — recheck every label or gather many examples? (a) recheck every label (b) gather many examples
2. 2.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to save paper (c) to make it bigger (d) to see if it learned
3. 3.📋 Planning an AI project: which comes first — fix it and test again or test on new photos? (a) fix it and test again (b) test on new photos
4. 4.❌ Diya’s spam spotter was tested on 40 new messages and got 36 right. How many did it get wrong?
5. 5.🎯 Arjun’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
6. 6.📋 Planning an AI project: which comes first — try unseen examples or fix it and test again? (a) try unseen examples (b) fix it and test again
7. 7.📦 Ananya collected 150 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
8. 8.📋 Planning an AI project: which comes first — fix it and test again or let it learn patterns? (a) fix it and test again (b) let it learn patterns
9. 9.📋 Planning an AI project: which comes first — split train and test or calculate percent right? (a) split train and test (b) calculate percent right
10. 10.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) more labelled examples (c) fewer examples (d) a new colour screen
11. 11.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 8 right and Model B got 6 right. How many percentage points more accurate is Model A?
12. 12.🧪 You can plan a simple AI project with… (a) a secret password (b) only a big robot (c) nothing at all (d) paper and examples
13. 13.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 7 right and Model B got 5 right. How many percentage points more accurate is Model A?
14. 14.📦 Rohan collected 80 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
15. 15.🎯 Nisha’s recycling sorter was tested on 5 new waste photos and got 5 right. What is its accuracy in percent?
16. 16.📋 Planning an AI project: which comes first — work out the accuracy or label each example? (a) work out the accuracy (b) label each example
17. 17.📦 Meera collected 200 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
18. 18.📋 Planning an AI project: which comes first — collect fruit photos or label each example? (a) collect fruit photos (b) label each example
19. 19.📋 Planning an AI project: which comes first — train the model or recheck every label? (a) train the model (b) recheck every label
20. 20.🧪 What is accuracy? (a) correct ÷ total × 100 (b) correct + total (c) total − correct (d) total × 2
21. 21.📋 Planning an AI project: which comes first — improve data, retest or work out the accuracy? (a) improve data, retest (b) work out the accuracy
22. 22.📋 Planning an AI project: which comes first — calculate percent right or test on new photos? (a) calculate percent right (b) test on new photos
23. 23.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 37 right and Model B got 26 right. How many percentage points more accurate is Model A?
24. 24.📋 Planning an AI project: which comes first — tag each photo by type or train the model? (a) tag each photo by type (b) train the model
25. 25.📋 Planning an AI project: which comes first — test on new photos or choose what to sort? (a) test on new photos (b) choose what to sort
26. 26.📋 Planning an AI project: which comes first — train the model or calculate percent right? (a) train the model (b) calculate percent right
27. 27.🎯 Kabir’s bird-song app is 50% accurate. If it is tested on 70 new bird songs, how many should it get right?
28. 28.🎯 Tara’s spam spotter is 50% accurate. If it is tested on 100 new messages, how many should it get right?
29. 29.🎯 Nisha’s leaf identifier is 60% accurate. If it is tested on 40 new leaf photos, how many should it get right?
30. 30.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 9 right and Model B got 5 right. How many percentage points more accurate is Model A?
31. 31.📋 Planning an AI project: which comes first — choose what to sort or split train and test? (a) choose what to sort (b) split train and test
32. 32.📦 Tara collected 150 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
33. 33.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 23 right and Model B got 14 right. How many percentage points more accurate is Model A?
34. 34.🎯 Nisha’s spam spotter is 50% accurate. If it is tested on 50 new messages, how many should it get right?
35. 35.🎯 Kabir’s spam spotter was tested on 10 new messages and got 8 right. What is its accuracy in percent?
36. 36.📋 Planning an AI project: which comes first — split train and test or try unseen examples? (a) split train and test (b) try unseen examples
37. 37.📋 Planning an AI project: which comes first — improve data, retest or try unseen examples? (a) improve data, retest (b) try unseen examples
38. 38.🎯 Meera’s fruit sorter is 90% accurate. If it is tested on 30 new fruit photos, how many should it get right?
39. 39.🎯 Saanvi’s leaf identifier is 70% accurate. If it is tested on 20 new leaf photos, how many should it get right?
40. 40.📦 Ananya collected 120 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?

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