Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 949 · 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.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 17 right and Model B got 16 right. How many percentage points more accurate is Model A?
2. 2.❌ Saanvi’s recycling sorter was tested on 13 new waste photos and got 11 right. How many did it get wrong?
3. 3.🎯 Nisha’s fruit sorter was tested on 25 new fruit photos and got 18 right. What is its accuracy in percent?
4. 4.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 10 right and Model B got 6 right. How many percentage points more accurate is Model A?
5. 5.📋 Planning an AI project: which comes first — pick a question to solve or work out the accuracy? (a) pick a question to solve (b) work out the accuracy
6. 6.🎯 Diya’s fruit sorter was tested on 10 new fruit photos and got 10 right. What is its accuracy in percent?
7. 7.📦 Diya collected 190 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
8. 8.❌ Nisha’s spam spotter was tested on 14 new messages and got 10 right. How many did it get wrong?
9. 9.📦 Rohan collected 110 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
10. 10.📦 Diya collected 60 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
11. 11.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) a louder speaker (c) a new colour screen (d) fewer examples
12. 12.🎯 Arjun’s leaf identifier was tested on 4 new leaf photos and got 2 right. What is its accuracy in percent?
13. 13.🎯 Arjun’s fruit sorter was tested on 25 new fruit photos and got 18 right. What is its accuracy in percent?
14. 14.📦 Ananya collected 130 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
15. 15.🧪 You can plan a simple AI project with… (a) nothing at all (b) only a big robot (c) a secret password (d) paper and examples
16. 16.🎯 Diya’s bird-song app is 90% accurate. If it is tested on 80 new bird songs, how many should it get right?
17. 17.❌ Diya’s spam spotter was tested on 41 new messages and got 35 right. How many did it get wrong?
18. 18.📦 Kabir collected 120 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
19. 19.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 18 right and Model B got 15 right. How many percentage points more accurate is Model A?
20. 20.🎯 Ishaan’s spam spotter was tested on 5 new messages and got 5 right. What is its accuracy in percent?
21. 21.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 25 right and Model B got 18 right. How many percentage points more accurate is Model A?
22. 22.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to see if it learned (c) to make it bigger (d) to make it faster
23. 23.📋 Planning an AI project: which comes first — improve data, retest or try unseen examples? (a) improve data, retest (b) try unseen examples
24. 24.📋 Planning an AI project: which comes first — recheck every label or gather many examples? (a) recheck every label (b) gather many examples
25. 25.📋 Planning an AI project: which comes first — improve data, retest or recheck every label? (a) improve data, retest (b) recheck every label
26. 26.🎯 Ananya’s handwriting reader was tested on 5 new handwritten letters and got 3 right. What is its accuracy in percent?
27. 27.📋 Planning an AI project: which comes first — pick a question to solve or test on new photos? (a) pick a question to solve (b) test on new photos
28. 28.🎯 Arjun’s handwriting reader was tested on 5 new handwritten letters and got 3 right. What is its accuracy in percent?
29. 29.📦 Ananya collected 120 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
30. 30.📋 Planning an AI project: which comes first — work out the accuracy or set aside test photos? (a) work out the accuracy (b) set aside test photos
31. 31.🎯 Ishaan’s fruit sorter was tested on 10 new fruit photos and got 9 right. What is its accuracy in percent?
32. 32.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct + total (d) correct ÷ total × 100
33. 33.❌ Saanvi’s fruit sorter was tested on 49 new fruit photos and got 41 right. How many did it get wrong?
34. 34.❌ Diya’s handwriting reader was tested on 47 new handwritten letters and got 42 right. How many did it get wrong?
35. 35.📋 Planning an AI project: which comes first — calculate percent right or recheck every label? (a) calculate percent right (b) recheck every label
36. 36.📋 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
37. 37.⚖️ Two fruit sorter models were tested on the same 50 fruit photos. Model A got 48 right and Model B got 47 right. How many percentage points more accurate is Model A?
38. 38.🎯 Arjun’s fruit sorter was tested on 50 new fruit photos and got 42 right. What is its accuracy in percent?
39. 39.🎯 Meera’s leaf identifier is 80% accurate. If it is tested on 60 new leaf photos, how many should it get right?
40. 40.📋 Planning an AI project: which comes first — correct bad labels or let it learn patterns? (a) correct bad labels (b) let it learn patterns

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