Build Your Own AI Project Worksheet
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.
NameDateTime takenScore ___ / 40
- 1.🧪 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
- 2.❌ Kabir’s spam spotter was tested on 47 new messages and got 45 right. How many did it get wrong?
- 3.🧪 What is accuracy? (a) total − correct (b) correct + total (c) total × 2 (d) correct ÷ total × 100
- 4.📦 Aarav collected 70 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
- 5.🎯 Aarav’s recycling sorter is 50% accurate. If it is tested on 100 new waste photos, how many should it get right?
- 6.🎯 Meera’s leaf identifier was tested on 50 new leaf photos and got 37 right. What is its accuracy in percent?
- 7.📋 Planning an AI project: which comes first — tag each photo by type or train the model? (a) tag each photo by type (b) train the model
- 8.📋 Planning an AI project: which comes first — correct bad labels or set aside test photos? (a) correct bad labels (b) set aside test photos
- 9.🎯 Diya’s recycling sorter is 50% accurate. If it is tested on 60 new waste photos, how many should it get right?
- 10.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
- 11.🎯 Arjun’s handwriting reader is 80% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
- 12.📋 Planning an AI project: which comes first — gather many examples or pick a question to solve? (a) gather many examples (b) pick a question to solve
- 13.📦 Nisha collected 100 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
- 14.📋 Planning an AI project: which comes first — label each example or split train and test? (a) label each example (b) split train and test
- 15.📋 Planning an AI project: which comes first — let it learn patterns or work out the accuracy? (a) let it learn patterns (b) work out the accuracy
- 16.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 47 right and Model B got 26 right. How many percentage points more accurate is Model A?
- 17.🎯 Diya’s spam spotter is 80% accurate. If it is tested on 70 new messages, how many should it get right?
- 18.📋 Planning an AI project: which comes first — try unseen examples or let it learn patterns? (a) try unseen examples (b) let it learn patterns
- 19.🎯 Arjun’s leaf identifier was tested on 20 new leaf photos and got 10 right. What is its accuracy in percent?
- 20.📋 Planning an AI project: which comes first — correct bad labels or collect fruit photos? (a) correct bad labels (b) collect fruit photos
- 21.🎯 Vihaan’s handwriting reader was tested on 5 new handwritten letters and got 3 right. What is its accuracy in percent?
- 22.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
- 23.🧪 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
- 24.📦 Vihaan collected 150 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 25.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 10 right and Model B got 8 right. How many percentage points more accurate is Model A?
- 26.🎯 Arjun’s fruit sorter was tested on 25 new fruit photos and got 16 right. What is its accuracy in percent?
- 27.📋 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
- 28.🎯 Aarav’s leaf identifier was tested on 4 new leaf photos and got 2 right. What is its accuracy in percent?
- 29.📋 Planning an AI project: which comes first — recheck every label or collect fruit photos? (a) recheck every label (b) collect fruit photos
- 30.📦 Meera collected 50 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
- 31.❌ Diya’s spam spotter was tested on 17 new messages and got 12 right. How many did it get wrong?
- 32.📦 Meera collected 80 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 33.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 22 right and Model B got 16 right. How many percentage points more accurate is Model A?
- 34.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to see if it learned (c) to save paper (d) to make it faster
- 35.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 49 right and Model B got 46 right. How many percentage points more accurate is Model A?
- 36.📋 Planning an AI project: which comes first — correct bad labels or improve data, retest? (a) correct bad labels (b) improve data, retest
- 37.🎯 Tara’s fruit sorter was tested on 5 new fruit photos and got 4 right. What is its accuracy in percent?
- 38.🎯 Saanvi’s handwriting reader was tested on 20 new handwritten letters and got 13 right. What is its accuracy in percent?
- 39.🎯 Diya’s fruit sorter was tested on 4 new fruit photos and got 2 right. What is its accuracy in percent?
- 40.📋 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
Answer key
- paper and examples
- 2
- correct ÷ total × 100
- 56
- 50
- 74
- tag each photo by type
- correct bad labels
- 30
- calculate percent right
- 24
- pick a question to solve
- 80
- label each example
- let it learn patterns
- 42
- 56
- let it learn patterns
- 50
- collect fruit photos
- 60
- test on new photos
- more labelled examples
- 120
- 20
- 64
- work out the accuracy
- 50
- collect fruit photos
- 40
- 5
- 64
- 24
- to see if it learned
- 6
- correct bad labels
- 80
- 65
- 50
- pick a question to solve
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students