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.📋 Planning an AI project: which comes first — fix it and test again or set aside test photos? (a) fix it and test again (b) set aside test photos
- 2.📋 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
- 3.❌ Saanvi’s handwriting reader was tested on 21 new handwritten letters and got 16 right. How many did it get wrong?
- 4.📦 Tara collected 130 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
- 5.📋 Planning an AI project: which comes first — work out the accuracy or correct bad labels? (a) work out the accuracy (b) correct bad labels
- 6.🎯 Kabir’s handwriting reader was tested on 20 new handwritten letters and got 12 right. What is its accuracy in percent?
- 7.📋 Planning an AI project: which comes first — tag each photo by type or fix it and test again? (a) tag each photo by type (b) fix it and test again
- 8.🎯 Meera’s leaf identifier is 80% accurate. If it is tested on 10 new leaf photos, how many should it get right?
- 9.🧪 What is accuracy? (a) correct ÷ total × 100 (b) total × 2 (c) correct + total (d) total − correct
- 10.📦 Kabir collected 50 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
- 11.❌ Saanvi’s bird-song app was tested on 24 new bird songs and got 20 right. How many did it get wrong?
- 12.📦 Meera collected 100 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 13.❌ Arjun’s recycling sorter was tested on 19 new waste photos and got 16 right. How many did it get wrong?
- 14.❌ Tara’s fruit sorter was tested on 21 new fruit photos and got 15 right. How many did it get wrong?
- 15.📋 Planning an AI project: which comes first — let it learn patterns or fix it and test again? (a) let it learn patterns (b) fix it and test again
- 16.📋 Planning an AI project: which comes first — improve data, retest or test on new photos? (a) improve data, retest (b) test on new photos
- 17.📋 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
- 18.📋 Planning an AI project: which comes first — pick a question to solve or set aside test photos? (a) pick a question to solve (b) set aside test photos
- 19.📋 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
- 20.📋 Planning an AI project: which comes first — train the model or label each example? (a) train the model (b) label each example
- 21.📋 Planning an AI project: which comes first — calculate percent right or try unseen examples? (a) calculate percent right (b) try unseen examples
- 22.📋 Planning an AI project: which comes first — choose what to sort or fix it and test again? (a) choose what to sort (b) fix it and test again
- 23.📦 Saanvi collected 120 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 24.🧪 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
- 25.🎯 Diya’s fruit sorter is 80% accurate. If it is tested on 30 new fruit photos, how many should it get right?
- 26.🎯 Kabir’s bird-song app was tested on 50 new bird songs and got 25 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.❌ Meera’s leaf identifier was tested on 50 new leaf photos and got 42 right. How many did it get wrong?
- 29.🎯 Ananya’s leaf identifier is 70% accurate. If it is tested on 60 new leaf photos, how many should it get right?
- 30.🎯 Meera’s spam spotter is 50% accurate. If it is tested on 50 new messages, how many should it get right?
- 31.📋 Planning an AI project: which comes first — collect fruit photos or tag each photo by type? (a) collect fruit photos (b) tag each photo by type
- 32.📋 Planning an AI project: which comes first — correct bad labels or improve data, retest? (a) correct bad labels (b) improve data, retest
- 33.📦 Diya collected 180 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 34.📋 Planning an AI project: which comes first — correct bad labels or collect fruit photos? (a) correct bad labels (b) collect fruit photos
- 35.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to save paper (c) to see if it learned (d) to make it bigger
- 36.📋 Planning an AI project: which comes first — choose what to sort or improve data, retest? (a) choose what to sort (b) improve data, retest
- 37.📋 Planning an AI project: which comes first — choose what to sort or set aside test photos? (a) choose what to sort (b) set aside test photos
- 38.📋 Planning an AI project: which comes first — set aside test photos or improve data, retest? (a) set aside test photos (b) improve data, retest
- 39.📋 Planning an AI project: which comes first — recheck every label or let it learn patterns? (a) recheck every label (b) let it learn patterns
- 40.🎯 Saanvi’s recycling sorter is 50% accurate. If it is tested on 90 new waste photos, how many should it get right?
Answer key
- set aside test photos
- tag each photo by type
- 5
- 104
- correct bad labels
- 60
- tag each photo by type
- 8
- correct ÷ total × 100
- 40
- 4
- 80
- 3
- 6
- let it learn patterns
- test on new photos
- pick a question to solve
- pick a question to solve
- let it learn patterns
- label each example
- try unseen examples
- choose what to sort
- 96
- more labelled examples
- 24
- 50
- work out the accuracy
- 8
- 42
- 25
- collect fruit photos
- correct bad labels
- 144
- collect fruit photos
- to see if it learned
- choose what to sort
- choose what to sort
- set aside test photos
- recheck every label
- 45
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students