Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 311 · 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.🎯 Ishaan’s fruit sorter is 90% accurate. If it is tested on 70 new fruit photos, how many should it get right?
2. 2.🧪 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
3. 3.📋 Planning an AI project: which comes first — train the model or correct bad labels? (a) train the model (b) correct bad labels
4. 4.📦 Meera collected 70 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
5. 5.🎯 Vihaan’s bird-song app is 90% accurate. If it is tested on 40 new bird songs, how many should it get right?
6. 6.🎯 Ananya’s fruit sorter is 50% accurate. If it is tested on 50 new fruit photos, how many should it get right?
7. 7.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 10 right and Model B got 6 right. How many percentage points more accurate is Model A?
8. 8.🧪 You can plan a simple AI project with… (a) only a big robot (b) nothing at all (c) a secret password (d) paper and examples
9. 9.📋 Planning an AI project: which comes first — train the model or collect fruit photos? (a) train the model (b) collect fruit photos
10. 10.📋 Planning an AI project: which comes first — test on new photos or train the model? (a) test on new photos (b) train the model
11. 11.⚖️ Two leaf identifier models were tested on the same 25 leaf photos. Model A got 23 right and Model B got 15 right. How many percentage points more accurate is Model A?
12. 12.🎯 Kabir’s bird-song app was tested on 50 new bird songs and got 33 right. What is its accuracy in percent?
13. 13.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 9 right and Model B got 7 right. How many percentage points more accurate is Model A?
14. 14.❌ Saanvi’s fruit sorter was tested on 25 new fruit photos and got 16 right. How many did it get wrong?
15. 15.📦 Nisha collected 180 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
16. 16.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 21 right and Model B got 16 right. How many percentage points more accurate is Model A?
17. 17.🎯 Aarav’s bird-song app is 70% accurate. If it is tested on 20 new bird songs, how many should it get right?
18. 18.❌ Ananya’s spam spotter was tested on 26 new messages and got 23 right. How many did it get wrong?
19. 19.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) more labelled examples (c) a louder speaker (d) fewer examples
20. 20.🎯 Kabir’s handwriting reader was tested on 10 new handwritten letters and got 10 right. What is its accuracy in percent?
21. 21.📋 Planning an AI project: which comes first — try unseen examples or let it learn patterns? (a) try unseen examples (b) let it learn patterns
22. 22.🎯 Ananya’s handwriting reader is 50% accurate. If it is tested on 50 new handwritten letters, how many should it get right?
23. 23.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
24. 24.📦 Vihaan collected 110 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
25. 25.⚖️ Two recycling sorter models were tested on the same 20 waste photos. Model A got 18 right and Model B got 10 right. How many percentage points more accurate is Model A?
26. 26.❌ Aarav’s handwriting reader was tested on 25 new handwritten letters and got 18 right. How many did it get wrong?
27. 27.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 18 right and Model B got 13 right. How many percentage points more accurate is Model A?
28. 28.📋 Planning an AI project: which comes first — pick a question to solve or let it learn patterns? (a) pick a question to solve (b) let it learn patterns
29. 29.🎯 Vihaan’s fruit sorter was tested on 50 new fruit photos and got 29 right. What is its accuracy in percent?
30. 30.📋 Planning an AI project: which comes first — fix it and test again or correct bad labels? (a) fix it and test again (b) correct bad labels
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’s bird-song app was tested on 10 new bird songs and got 6 right. What is its accuracy in percent?
33. 33.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 23 right and Model B got 16 right. How many percentage points more accurate is Model A?
34. 34.🎯 Kabir’s recycling sorter is 80% accurate. If it is tested on 80 new waste photos, how many should it get right?
35. 35.📋 Planning an AI project: which comes first — split train and test or recheck every label? (a) split train and test (b) recheck every label
36. 36.🎯 Kabir’s spam spotter is 50% accurate. If it is tested on 70 new messages, how many should it get right?
37. 37.❌ Kabir’s fruit sorter was tested on 27 new fruit photos and got 20 right. How many did it get wrong?
38. 38.📋 Planning an AI project: which comes first — train the model or test on new photos? (a) train the model (b) test on new photos
39. 39.📦 Ishaan collected 130 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
40. 40.📋 Planning an AI project: which comes first — improve data, retest or label each example? (a) improve data, retest (b) label each example

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