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.🎯 Nisha’s bird-song app was tested on 50 new bird songs and got 31 right. What is its accuracy in percent?
- 2.📋 Planning an AI project: which comes first — correct bad labels or improve data, retest? (a) correct bad labels (b) improve data, retest
- 3.🧪 What is accuracy? (a) total × 2 (b) correct + total (c) total − correct (d) correct ÷ total × 100
- 4.🎯 Aarav’s handwriting reader is 80% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
- 5.📦 Saanvi collected 110 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 6.🎯 Nisha’s fruit sorter was tested on 10 new fruit photos and got 6 right. What is its accuracy in percent?
- 7.📦 Diya collected 130 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
- 8.📦 Meera collected 150 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 9.❌ Saanvi’s bird-song app was tested on 21 new bird songs and got 20 right. How many did it get wrong?
- 10.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to save paper (c) to make it faster (d) to see if it learned
- 11.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 49 right and Model B got 48 right. How many percentage points more accurate is Model A?
- 12.🧪 You can plan a simple AI project with… (a) a secret password (b) nothing at all (c) only a big robot (d) paper and examples
- 13.📦 Meera collected 170 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 14.📋 Planning an AI project: which comes first — improve data, retest or try unseen examples? (a) improve data, retest (b) try unseen examples
- 15.❌ Rohan’s spam spotter was tested on 16 new messages and got 12 right. How many did it get wrong?
- 16.📦 Vihaan collected 120 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
- 17.📦 Tara collected 100 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
- 18.❌ Diya’s leaf identifier was tested on 21 new leaf photos and got 18 right. How many did it get wrong?
- 19.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 22 right and Model B got 15 right. How many percentage points more accurate is Model A?
- 20.📋 Planning an AI project: which comes first — train the model or improve data, retest? (a) train the model (b) improve data, retest
- 21.📋 Planning an AI project: which comes first — pick a question to solve or split train and test? (a) pick a question to solve (b) split train and test
- 22.🎯 Ananya’s bird-song app was tested on 4 new bird songs and got 3 right. What is its accuracy in percent?
- 23.🎯 Aarav’s spam spotter was tested on 20 new messages and got 17 right. What is its accuracy in percent?
- 24.📋 Planning an AI project: which comes first — recheck every label or tag each photo by type? (a) recheck every label (b) tag each photo by type
- 25.❌ Meera’s spam spotter was tested on 31 new messages and got 22 right. How many did it get wrong?
- 26.🎯 Kabir’s leaf identifier is 60% accurate. If it is tested on 70 new leaf photos, how many should it get right?
- 27.📦 Kabir collected 60 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
- 28.❌ Rohan’s leaf identifier was tested on 22 new leaf photos and got 15 right. How many did it get wrong?
- 29.🎯 Aarav’s spam spotter was tested on 10 new messages and got 5 right. What is its accuracy in percent?
- 30.🎯 Nisha’s fruit sorter was tested on 20 new fruit photos and got 13 right. What is its accuracy in percent?
- 31.📋 Planning an AI project: which comes first — choose what to sort or improve data, retest? (a) choose what to sort (b) improve data, retest
- 32.🎯 Kabir’s handwriting reader was tested on 25 new handwritten letters and got 13 right. What is its accuracy in percent?
- 33.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) fewer examples (c) a louder speaker (d) more labelled examples
- 34.📋 Planning an AI project: which comes first — test on new photos or let it learn patterns? (a) test on new photos (b) let it learn patterns
- 35.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 15 right and Model B got 11 right. How many percentage points more accurate is Model A?
- 36.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 18 right and Model B got 12 right. How many percentage points more accurate is Model A?
- 37.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 48 right and Model B got 43 right. How many percentage points more accurate is Model A?
- 38.⚖️ Two handwriting reader models were tested on the same 20 handwritten letters. Model A got 17 right and Model B got 11 right. How many percentage points more accurate is Model A?
- 39.📋 Planning an AI project: which comes first — collect fruit photos or train the model? (a) collect fruit photos (b) train the model
- 40.📋 Planning an AI project: which comes first — train the model or try unseen examples? (a) train the model (b) try unseen examples
Answer key
- 62
- correct bad labels
- correct ÷ total × 100
- 24
- 88
- 60
- 104
- 120
- 1
- to see if it learned
- 2
- paper and examples
- 136
- try unseen examples
- 4
- 96
- 80
- 3
- 28
- train the model
- pick a question to solve
- 75
- 85
- tag each photo by type
- 9
- 42
- 48
- 7
- 50
- 65
- choose what to sort
- 52
- more labelled examples
- let it learn patterns
- 20
- 30
- 10
- 30
- collect fruit photos
- train the model
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students