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) a secret password (b) only a big robot (c) paper and examples (d) nothing at all
- 2.📋 Planning an AI project: which comes first — calculate percent right or gather many examples? (a) calculate percent right (b) gather many examples
- 3.🎯 Kabir’s bird-song app is 70% accurate. If it is tested on 30 new bird songs, how many should it get right?
- 4.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 6 right and Model B got 5 right. How many percentage points more accurate is Model A?
- 5.🧪 What is accuracy? (a) correct + total (b) total − correct (c) correct ÷ total × 100 (d) total × 2
- 6.📋 Planning an AI project: which comes first — train the model or recheck every label? (a) train the model (b) recheck every label
- 7.📦 Vihaan collected 90 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
- 8.📋 Planning an AI project: which comes first — test on new photos or work out the accuracy? (a) test on new photos (b) work out the accuracy
- 9.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 9 right and Model B got 8 right. How many percentage points more accurate is Model A?
- 10.📋 Planning an AI project: which comes first — test on new photos or tag each photo by type? (a) test on new photos (b) tag each photo by type
- 11.📋 Planning an AI project: which comes first — pick a question to solve or collect fruit photos? (a) pick a question to solve (b) collect fruit photos
- 12.❌ Arjun’s leaf identifier was tested on 19 new leaf photos and got 14 right. How many did it get wrong?
- 13.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to make it faster (c) to see if it learned (d) to save paper
- 14.📋 Planning an AI project: which comes first — recheck every label or pick a question to solve? (a) recheck every label (b) pick a question to solve
- 15.📋 Planning an AI project: which comes first — test on new photos or set aside test photos? (a) test on new photos (b) set aside test photos
- 16.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) a louder speaker (c) more labelled examples (d) a new colour screen
- 17.🎯 Nisha’s bird-song app was tested on 50 new bird songs and got 42 right. What is its accuracy in percent?
- 18.📦 Diya collected 40 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
- 19.🎯 Meera’s fruit sorter was tested on 20 new fruit photos and got 18 right. What is its accuracy in percent?
- 20.📦 Tara collected 200 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
- 21.📋 Planning an AI project: which comes first — pick a question to solve or correct bad labels? (a) pick a question to solve (b) correct bad labels
- 22.🎯 Aarav’s leaf identifier is 80% accurate. If it is tested on 50 new leaf photos, how many should it get right?
- 23.❌ Arjun’s fruit sorter was tested on 34 new fruit photos and got 27 right. How many did it get wrong?
- 24.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 8 right. How many percentage points more accurate is Model A?
- 25.🎯 Meera’s bird-song app was tested on 4 new bird songs and got 3 right. What is its accuracy in percent?
- 26.📋 Planning an AI project: which comes first — improve data, retest or correct bad labels? (a) improve data, retest (b) correct bad labels
- 27.❌ Kabir’s fruit sorter was tested on 28 new fruit photos and got 20 right. How many did it get wrong?
- 28.🎯 Arjun’s recycling sorter was tested on 4 new waste photos and got 2 right. What is its accuracy in percent?
- 29.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 20 right and Model B got 19 right. How many percentage points more accurate is Model A?
- 30.🎯 Nisha’s recycling sorter is 50% accurate. If it is tested on 50 new waste photos, how many should it get right?
- 31.📋 Planning an AI project: which comes first — choose what to sort or calculate percent right? (a) choose what to sort (b) calculate percent right
- 32.📦 Meera collected 60 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
- 33.❌ Meera’s spam spotter was tested on 20 new messages and got 17 right. How many did it get wrong?
- 34.📋 Planning an AI project: which comes first — calculate percent right or train the model? (a) calculate percent right (b) train the model
- 35.📋 Planning an AI project: which comes first — calculate percent right or choose what to sort? (a) calculate percent right (b) choose what to sort
- 36.📋 Planning an AI project: which comes first — fix it and test again or test on new photos? (a) fix it and test again (b) test on new photos
- 37.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 34 right and Model B got 32 right. How many percentage points more accurate is Model A?
- 38.📋 Planning an AI project: which comes first — test on new photos or collect fruit photos? (a) test on new photos (b) collect fruit photos
- 39.📦 Aarav collected 80 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
- 40.🎯 Saanvi’s bird-song app is 60% accurate. If it is tested on 90 new bird songs, how many should it get right?
Answer key
- paper and examples
- gather many examples
- 21
- 10
- correct ÷ total × 100
- recheck every label
- 72
- test on new photos
- 10
- tag each photo by type
- pick a question to solve
- 5
- to see if it learned
- pick a question to solve
- set aside test photos
- more labelled examples
- 84
- 32
- 90
- 160
- pick a question to solve
- 40
- 7
- 20
- 75
- correct bad labels
- 8
- 50
- 4
- 25
- choose what to sort
- 48
- 3
- train the model
- choose what to sort
- test on new photos
- 4
- collect fruit photos
- 64
- 54
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students