Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 644 · 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 — collect fruit photos or train the model? (a) collect fruit photos (b) train the model
2. 2.🎯 Kabir’s leaf identifier was tested on 4 new leaf photos and got 2 right. What is its accuracy in percent?
3. 3.📦 Ananya collected 150 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
4. 4.🎯 Vihaan’s handwriting reader is 60% accurate. If it is tested on 20 new handwritten letters, how many should it get right?
5. 5.🧪 You can plan a simple AI project with… (a) nothing at all (b) a secret password (c) paper and examples (d) only a big robot
6. 6.📋 Planning an AI project: which comes first — improve data, retest or train the model? (a) improve data, retest (b) train the model
7. 7.📋 Planning an AI project: which comes first — try unseen examples or let it learn patterns? (a) try unseen examples (b) let it learn patterns
8. 8.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 19 right and Model B got 18 right. How many percentage points more accurate is Model A?
9. 9.🧪 What is accuracy? (a) correct + total (b) total − correct (c) correct ÷ total × 100 (d) total × 2
10. 10.📋 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
11. 11.📋 Planning an AI project: which comes first — try unseen examples or set aside test photos? (a) try unseen examples (b) set aside test photos
12. 12.📋 Planning an AI project: which comes first — let it learn patterns or split train and test? (a) let it learn patterns (b) split train and test
13. 13.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 10 right and Model B got 5 right. How many percentage points more accurate is Model A?
14. 14.🎯 Kabir’s leaf identifier is 70% accurate. If it is tested on 40 new leaf photos, how many should it get right?
15. 15.📋 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
16. 16.❌ Ishaan’s handwriting reader was tested on 42 new handwritten letters and got 37 right. How many did it get wrong?
17. 17.❌ Tara’s spam spotter was tested on 12 new messages and got 10 right. How many did it get wrong?
18. 18.📋 Planning an AI project: which comes first — correct bad labels or try unseen examples? (a) correct bad labels (b) try unseen examples
19. 19.📋 Planning an AI project: which comes first — let it learn patterns or calculate percent right? (a) let it learn patterns (b) calculate percent right
20. 20.📋 Planning an AI project: which comes first — tag each photo by type or pick a question to solve? (a) tag each photo by type (b) pick a question to solve
21. 21.🎯 Meera’s fruit sorter was tested on 50 new fruit photos and got 42 right. What is its accuracy in percent?
22. 22.❌ Diya’s handwriting reader was tested on 29 new handwritten letters and got 27 right. How many did it get wrong?
23. 23.📦 Tara collected 90 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
24. 24.❌ Diya’s recycling sorter was tested on 16 new waste photos and got 12 right. How many did it get wrong?
25. 25.📦 Arjun collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
26. 26.🎯 Meera’s handwriting reader was tested on 25 new handwritten letters and got 20 right. What is its accuracy in percent?
27. 27.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 40 right and Model B got 39 right. How many percentage points more accurate is Model A?
28. 28.📋 Planning an AI project: which comes first — work out the accuracy or train the model? (a) work out the accuracy (b) train the model
29. 29.📋 Planning an AI project: which comes first — train the model or improve data, retest? (a) train the model (b) improve data, retest
30. 30.📋 Planning an AI project: which comes first — correct bad labels or set aside test photos? (a) correct bad labels (b) set aside test photos
31. 31.🧪 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
32. 32.🎯 Rohan’s recycling sorter was tested on 25 new waste photos and got 18 right. What is its accuracy in percent?
33. 33.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 6 right and Model B got 5 right. How many percentage points more accurate is Model A?
34. 34.📦 Kabir collected 140 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
35. 35.🎯 Meera’s fruit sorter was tested on 4 new fruit photos and got 2 right. What is its accuracy in percent?
36. 36.🎯 Ishaan’s bird-song app is 50% accurate. If it is tested on 70 new bird songs, how many should it get right?
37. 37.📋 Planning an AI project: which comes first — train the model or correct bad labels? (a) train the model (b) correct bad labels
38. 38.🎯 Rohan’s recycling sorter was tested on 50 new waste photos and got 46 right. What is its accuracy in percent?
39. 39.📋 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
40. 40.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to save paper (c) to make it faster (d) to make it bigger

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