Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 840 · 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 — try unseen examples or fix it and test again? (a) try unseen examples (b) fix it and test again
2. 2.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) more labelled examples (c) a louder speaker (d) a new colour screen
3. 3.📋 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
4. 4.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to see if it learned (c) to make it bigger (d) to save paper
5. 5.📦 Kabir collected 50 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
6. 6.🧪 What is accuracy? (a) total − correct (b) correct ÷ total × 100 (c) correct + total (d) total × 2
7. 7.🎯 Meera’s spam spotter was tested on 20 new messages and got 17 right. What is its accuracy in percent?
8. 8.🎯 Ananya’s bird-song app is 70% accurate. If it is tested on 70 new bird songs, how many should it get right?
9. 9.❌ Aarav’s handwriting reader was tested on 39 new handwritten letters and got 34 right. How many did it get wrong?
10. 10.📋 Planning an AI project: which comes first — improve data, retest or set aside test photos? (a) improve data, retest (b) set aside test photos
11. 11.📋 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
12. 12.❌ Ishaan’s leaf identifier was tested on 38 new leaf photos and got 36 right. How many did it get wrong?
13. 13.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 9 right and Model B got 8 right. How many percentage points more accurate is Model A?
14. 14.🎯 Nisha’s recycling sorter is 50% accurate. If it is tested on 10 new waste photos, how many should it get right?
15. 15.🎯 Ishaan’s fruit sorter is 70% accurate. If it is tested on 40 new fruit photos, how many should it get right?
16. 16.📋 Planning an AI project: which comes first — train the model or label each example? (a) train the model (b) label each example
17. 17.📋 Planning an AI project: which comes first — split train and test or fix it and test again? (a) split train and test (b) fix it and test again
18. 18.📋 Planning an AI project: which comes first — work out the accuracy or gather many examples? (a) work out the accuracy (b) gather many examples
19. 19.📋 Planning an AI project: which comes first — test on new photos or set aside test photos? (a) test on new photos (b) set aside test photos
20. 20.📋 Planning an AI project: which comes first — correct bad labels or collect fruit photos? (a) correct bad labels (b) collect fruit photos
21. 21.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 34 right and Model B got 30 right. How many percentage points more accurate is Model A?
22. 22.📋 Planning an AI project: which comes first — improve data, retest or gather many examples? (a) improve data, retest (b) gather many examples
23. 23.🎯 Ishaan’s bird-song app was tested on 25 new bird songs and got 20 right. What is its accuracy in percent?
24. 24.📋 Planning an AI project: which comes first — tag each photo by type or correct bad labels? (a) tag each photo by type (b) correct bad labels
25. 25.📋 Planning an AI project: which comes first — improve data, retest or try unseen examples? (a) improve data, retest (b) try unseen examples
26. 26.📦 Ishaan collected 170 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
27. 27.🎯 Vihaan’s spam spotter is 90% accurate. If it is tested on 80 new messages, how many should it get right?
28. 28.📦 Rohan collected 130 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
29. 29.🎯 Rohan’s recycling sorter is 70% accurate. If it is tested on 50 new waste photos, how many should it get right?
30. 30.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 43 right and Model B got 30 right. How many percentage points more accurate is Model A?
31. 31.📦 Nisha collected 70 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
32. 32.❌ Arjun’s handwriting reader was tested on 42 new handwritten letters and got 37 right. How many did it get wrong?
33. 33.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 48 right and Model B got 41 right. How many percentage points more accurate is Model A?
34. 34.🎯 Arjun’s handwriting reader is 60% accurate. If it is tested on 90 new handwritten letters, how many should it get right?
35. 35.🎯 Aarav’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
36. 36.❌ Tara’s spam spotter was tested on 35 new messages and got 32 right. How many did it get wrong?
37. 37.🎯 Ananya’s leaf identifier was tested on 5 new leaf photos and got 4 right. What is its accuracy in percent?
38. 38.📋 Planning an AI project: which comes first — work out the accuracy or fix it and test again? (a) work out the accuracy (b) fix it and test again
39. 39.📦 Meera collected 80 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
40. 40.📋 Planning an AI project: which comes first — choose what to sort or calculate percent right? (a) choose what to sort (b) calculate percent right

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