Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 959 · 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 fruit sorter was tested on 32 new fruit photos and got 29 right. How many did it get wrong?
2. 2.🧪 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
3. 3.❌ Kabir’s fruit sorter was tested on 14 new fruit photos and got 11 right. How many did it get wrong?
4. 4.📋 Planning an AI project: which comes first — let it learn patterns or gather many examples? (a) let it learn patterns (b) gather many examples
5. 5.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 19 right and Model B got 18 right. How many percentage points more accurate is Model A?
6. 6.📋 Planning an AI project: which comes first — work out the accuracy or let it learn patterns? (a) work out the accuracy (b) let it learn patterns
7. 7.❌ Ishaan’s bird-song app was tested on 48 new bird songs and got 45 right. How many did it get wrong?
8. 8.📋 Planning an AI project: which comes first — gather many examples or train the model? (a) gather many examples (b) train the model
9. 9.📋 Planning an AI project: which comes first — collect fruit photos or label each example? (a) collect fruit photos (b) label each example
10. 10.❌ Vihaan’s leaf identifier was tested on 15 new leaf photos and got 11 right. How many did it get wrong?
11. 11.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 7 right and Model B got 5 right. How many percentage points more accurate is Model A?
12. 12.🧪 You can plan a simple AI project with… (a) nothing at all (b) a secret password (c) only a big robot (d) paper and examples
13. 13.🧪 What is accuracy? (a) total − correct (b) correct + total (c) correct ÷ total × 100 (d) total × 2
14. 14.📋 Planning an AI project: which comes first — recheck every label or test on new photos? (a) recheck every label (b) test on new photos
15. 15.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 36 right and Model B got 30 right. How many percentage points more accurate is Model A?
16. 16.📋 Planning an AI project: which comes first — fix it and test again or work out the accuracy? (a) fix it and test again (b) work out the accuracy
17. 17.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) a louder speaker (c) more labelled examples (d) fewer examples
18. 18.❌ Ishaan’s recycling sorter was tested on 30 new waste photos and got 23 right. How many did it get wrong?
19. 19.🎯 Ananya’s recycling sorter was tested on 5 new waste photos and got 3 right. What is its accuracy in percent?
20. 20.🎯 Nisha’s fruit sorter was tested on 50 new fruit photos and got 33 right. What is its accuracy in percent?
21. 21.📋 Planning an AI project: which comes first — let it learn patterns or test on new photos? (a) let it learn patterns (b) test on new photos
22. 22.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 30 right and Model B got 29 right. How many percentage points more accurate is Model A?
23. 23.🎯 Ananya’s fruit sorter is 50% accurate. If it is tested on 90 new fruit photos, how many should it get right?
24. 24.⚖️ Two fruit sorter models were tested on the same 50 fruit photos. Model A got 46 right and Model B got 39 right. How many percentage points more accurate is Model A?
25. 25.📋 Planning an AI project: which comes first — fix it and test again or pick a question to solve? (a) fix it and test again (b) pick a question to solve
26. 26.📦 Tara collected 180 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
27. 27.📋 Planning an AI project: which comes first — label each example or work out the accuracy? (a) label each example (b) work out the accuracy
28. 28.🎯 Aarav’s leaf identifier was tested on 4 new leaf photos and got 4 right. What is its accuracy in percent?
29. 29.🎯 Tara’s recycling sorter is 60% accurate. If it is tested on 100 new waste photos, how many should it get right?
30. 30.📋 Planning an AI project: which comes first — pick a question to solve or label each example? (a) pick a question to solve (b) label each example
31. 31.📋 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
32. 32.🎯 Rohan’s handwriting reader is 80% accurate. If it is tested on 50 new handwritten letters, how many should it get right?
33. 33.📋 Planning an AI project: which comes first — correct bad labels or train the model? (a) correct bad labels (b) train the model
34. 34.📋 Planning an AI project: which comes first — label each example or fix it and test again? (a) label each example (b) fix it and test again
35. 35.🎯 Meera’s fruit sorter was tested on 5 new fruit photos and got 3 right. What is its accuracy in percent?
36. 36.🎯 Nisha’s leaf identifier was tested on 25 new leaf photos and got 23 right. What is its accuracy in percent?
37. 37.📋 Planning an AI project: which comes first — tag each photo by type or work out the accuracy? (a) tag each photo by type (b) work out the accuracy
38. 38.❌ Aarav’s handwriting reader was tested on 24 new handwritten letters and got 23 right. How many did it get wrong?
39. 39.❌ Kabir’s spam spotter was tested on 33 new messages and got 26 right. How many did it get wrong?
40. 40.📋 Planning an AI project: which comes first — work out the accuracy or try unseen examples? (a) work out the accuracy (b) try unseen examples

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students