Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 423 · 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.❌ Saanvi’s leaf identifier was tested on 37 new leaf photos and got 34 right. How many did it get wrong?
2. 2.🎯 Aarav’s bird-song app was tested on 25 new bird songs and got 22 right. What is its accuracy in percent?
3. 3.📦 Diya collected 140 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
4. 4.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to see if it learned (c) to save paper (d) to make it faster
5. 5.📋 Planning an AI project: which comes first — train the model or choose what to sort? (a) train the model (b) choose what to sort
6. 6.📋 Planning an AI project: which comes first — split train and test or recheck every label? (a) split train and test (b) recheck every label
7. 7.📋 Planning an AI project: which comes first — improve data, retest or work out the accuracy? (a) improve data, retest (b) work out the accuracy
8. 8.📦 Kabir collected 200 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
9. 9.🎯 Arjun’s leaf identifier was tested on 25 new leaf photos and got 25 right. What is its accuracy in percent?
10. 10.🎯 Meera’s spam spotter was tested on 50 new messages and got 32 right. What is its accuracy in percent?
11. 11.📋 Planning an AI project: which comes first — try unseen examples or improve data, retest? (a) try unseen examples (b) improve data, retest
12. 12.📋 Planning an AI project: which comes first — try unseen examples or recheck every label? (a) try unseen examples (b) recheck every label
13. 13.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
14. 14.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) a new colour screen (c) fewer examples (d) more labelled examples
15. 15.📋 Planning an AI project: which comes first — let it learn patterns or fix it and test again? (a) let it learn patterns (b) fix it and test again
16. 16.📦 Ananya collected 180 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
17. 17.🧪 You can plan a simple AI project with… (a) a secret password (b) nothing at all (c) only a big robot (d) paper and examples
18. 18.📋 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
19. 19.🎯 Saanvi’s leaf identifier was tested on 10 new leaf photos and got 10 right. What is its accuracy in percent?
20. 20.🎯 Meera’s fruit sorter is 90% accurate. If it is tested on 20 new fruit photos, how many should it get right?
21. 21.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 21 right and Model B got 20 right. How many percentage points more accurate is Model A?
22. 22.🎯 Rohan’s spam spotter is 50% accurate. If it is tested on 50 new messages, how many should it get right?
23. 23.📦 Ananya collected 120 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
24. 24.🎯 Meera’s fruit sorter was tested on 4 new fruit photos and got 3 right. What is its accuracy in percent?
25. 25.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
26. 26.📦 Kabir collected 170 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
27. 27.📋 Planning an AI project: which comes first — improve data, retest or train the model? (a) improve data, retest (b) train the model
28. 28.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 45 right and Model B got 44 right. How many percentage points more accurate is Model A?
29. 29.🎯 Rohan’s fruit sorter is 60% accurate. If it is tested on 100 new fruit photos, how many should it get right?
30. 30.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 24 right and Model B got 16 right. How many percentage points more accurate is Model A?
31. 31.🎯 Tara’s handwriting reader was tested on 25 new handwritten letters and got 17 right. What is its accuracy in percent?
32. 32.📋 Planning an AI project: which comes first — improve data, retest or correct bad labels? (a) improve data, retest (b) correct bad labels
33. 33.📦 Tara collected 50 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
34. 34.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 12 right and Model B got 10 right. How many percentage points more accurate is Model A?
35. 35.📋 Planning an AI project: which comes first — collect fruit photos or calculate percent right? (a) collect fruit photos (b) calculate percent right
36. 36.🎯 Diya’s spam spotter is 60% accurate. If it is tested on 30 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 49 right and Model B got 41 right. How many percentage points more accurate is Model A?
38. 38.❌ Diya’s bird-song app was tested on 33 new bird songs and got 26 right. How many did it get wrong?
39. 39.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct + total (d) correct ÷ total × 100
40. 40.📦 Arjun collected 100 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?

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