Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 454 · 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.🎯 Aarav’s spam spotter is 70% accurate. If it is tested on 10 new messages, how many should it get right?
2. 2.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct ÷ total × 100 (d) correct + total
3. 3.📋 Planning an AI project: which comes first — test on new photos or collect fruit photos? (a) test on new photos (b) collect fruit photos
4. 4.❌ Aarav’s leaf identifier was tested on 28 new leaf photos and got 27 right. How many did it get wrong?
5. 5.🎯 Saanvi’s spam spotter is 80% accurate. If it is tested on 80 new messages, how many should it get right?
6. 6.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 10 right and Model B got 5 right. How many percentage points more accurate is Model A?
7. 7.❌ Ananya’s spam spotter was tested on 43 new messages and got 37 right. How many did it get wrong?
8. 8.🎯 Diya’s recycling sorter is 80% accurate. If it is tested on 40 new waste photos, how many should it get right?
9. 9.🧪 You can plan a simple AI project with… (a) a secret password (b) nothing at all (c) paper and examples (d) only a big robot
10. 10.📋 Planning an AI project: which comes first — correct bad labels or improve data, retest? (a) correct bad labels (b) improve data, retest
11. 11.📦 Ishaan collected 40 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
12. 12.❌ Arjun’s bird-song app was tested on 23 new bird songs and got 22 right. How many did it get wrong?
13. 13.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to make it bigger (c) to save paper (d) to make it faster
14. 14.📋 Planning an AI project: which comes first — calculate percent right or choose what to sort? (a) calculate percent right (b) choose what to sort
15. 15.📦 Saanvi collected 60 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
16. 16.🎯 Kabir’s handwriting reader is 70% accurate. If it is tested on 80 new handwritten letters, how many should it get right?
17. 17.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
18. 18.📋 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
19. 19.📦 Nisha collected 120 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
20. 20.🎯 Saanvi’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
21. 21.📋 Planning an AI project: which comes first — train the model or label each example? (a) train the model (b) label each example
22. 22.❌ Diya’s fruit sorter was tested on 40 new fruit photos and got 31 right. How many did it get wrong?
23. 23.🎯 Tara’s leaf identifier is 50% accurate. If it is tested on 50 new leaf photos, how many should it get right?
24. 24.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
25. 25.🎯 Nisha’s fruit sorter was tested on 50 new fruit photos and got 39 right. What is its accuracy in percent?
26. 26.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 40 right and Model B got 35 right. How many percentage points more accurate is Model A?
27. 27.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) fewer examples (c) more labelled examples (d) a new colour screen
28. 28.🎯 Saanvi’s leaf identifier is 80% accurate. If it is tested on 20 new leaf photos, how many should it get right?
29. 29.📋 Planning an AI project: which comes first — label each example or calculate percent right? (a) label each example (b) calculate percent right
30. 30.🎯 Nisha’s leaf identifier was tested on 50 new leaf photos and got 47 right. What is its accuracy in percent?
31. 31.❌ Rohan’s fruit sorter was tested on 13 new fruit photos and got 11 right. How many did it get wrong?
32. 32.⚖️ Two spam spotter models were tested on the same 20 messages. Model A got 20 right and Model B got 18 right. How many percentage points more accurate is Model A?
33. 33.📋 Planning an AI project: which comes first — set aside test photos or let it learn patterns? (a) set aside test photos (b) let it learn patterns
34. 34.❌ Tara’s handwriting reader was tested on 26 new handwritten letters and got 21 right. How many did it get wrong?
35. 35.🎯 Vihaan’s recycling sorter was tested on 50 new waste photos and got 29 right. What is its accuracy in percent?
36. 36.📋 Planning an AI project: which comes first — collect fruit photos or choose what to sort? (a) collect fruit photos (b) choose what to sort
37. 37.📦 Vihaan collected 200 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
38. 38.📋 Planning an AI project: which comes first — calculate percent right or set aside test photos? (a) calculate percent right (b) set aside test photos
39. 39.🎯 Tara’s recycling sorter was tested on 20 new waste photos and got 14 right. What is its accuracy in percent?
40. 40.🎯 Aarav’s fruit sorter is 50% accurate. If it is tested on 10 new fruit photos, how many should it get right?

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