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 collect fruit photos? (a) fix it and test again (b) collect fruit photos
- 2.📋 Planning an AI project: which comes first — calculate percent right or label each example? (a) calculate percent right (b) label each example
- 3.🎯 Tara’s spam spotter was tested on 20 new messages and got 10 right. What is its accuracy in percent?
- 4.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to save paper (c) to make it faster (d) to make it bigger
- 5.❌ Arjun’s handwriting reader was tested on 32 new handwritten letters and got 28 right. How many did it get wrong?
- 6.📋 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
- 7.📋 Planning an AI project: which comes first — set aside test photos or label each example? (a) set aside test photos (b) label each example
- 8.🧪 You can plan a simple AI project with… (a) only a big robot (b) paper and examples (c) nothing at all (d) a secret password
- 9.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) a new colour screen (c) a louder speaker (d) more labelled examples
- 10.🎯 Aarav’s handwriting reader is 80% accurate. If it is tested on 20 new handwritten letters, how many should it get right?
- 11.📋 Planning an AI project: which comes first — correct bad labels or tag each photo by type? (a) correct bad labels (b) tag each photo by type
- 12.❌ Tara’s fruit sorter was tested on 19 new fruit photos and got 14 right. How many did it get wrong?
- 13.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 19 right and Model B got 18 right. How many percentage points more accurate is Model A?
- 14.📋 Planning an AI project: which comes first — pick a question to solve or improve data, retest? (a) pick a question to solve (b) improve data, retest
- 15.📋 Planning an AI project: which comes first — calculate percent right or try unseen examples? (a) calculate percent right (b) try unseen examples
- 16.🎯 Kabir’s fruit sorter is 60% accurate. If it is tested on 30 new fruit photos, how many should it get right?
- 17.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct + total (d) correct ÷ total × 100
- 18.🎯 Nisha’s spam spotter is 80% accurate. If it is tested on 70 new messages, how many should it get right?
- 19.📋 Planning an AI project: which comes first — calculate percent right or collect fruit photos? (a) calculate percent right (b) collect fruit photos
- 20.❌ Saanvi’s fruit sorter was tested on 27 new fruit photos and got 22 right. How many did it get wrong?
- 21.📋 Planning an AI project: which comes first — calculate percent right or train the model? (a) calculate percent right (b) train the model
- 22.⚖️ 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?
- 23.📋 Planning an AI project: which comes first — calculate percent right or test on new photos? (a) calculate percent right (b) test on new photos
- 24.🎯 Ishaan’s bird-song app is 70% accurate. If it is tested on 20 new bird songs, how many should it get right?
- 25.📦 Nisha collected 90 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
- 26.📋 Planning an AI project: which comes first — try unseen examples or label each example? (a) try unseen examples (b) label each example
- 27.📋 Planning an AI project: which comes first — correct bad labels or train the model? (a) correct bad labels (b) train the model
- 28.🎯 Rohan’s recycling sorter is 60% accurate. If it is tested on 60 new waste photos, how many should it get right?
- 29.🎯 Saanvi’s fruit sorter was tested on 10 new fruit photos and got 6 right. What is its accuracy in percent?
- 30.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 16 right and Model B got 14 right. How many percentage points more accurate is Model A?
- 31.📦 Ananya collected 40 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
- 32.🎯 Arjun’s fruit sorter was tested on 4 new fruit photos and got 2 right. What is its accuracy in percent?
- 33.📋 Planning an AI project: which comes first — calculate percent right or fix it and test again? (a) calculate percent right (b) fix it and test again
- 34.📦 Ananya collected 130 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
- 35.📋 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
- 36.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 7 right and Model B got 6 right. How many percentage points more accurate is Model A?
- 37.🎯 Diya’s spam spotter is 80% accurate. If it is tested on 10 new messages, how many should it get right?
- 38.📦 Rohan collected 60 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
- 39.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 47 right and Model B got 43 right. How many percentage points more accurate is Model A?
- 40.⚖️ Two recycling sorter models were tested on the same 20 waste photos. Model A got 18 right and Model B got 17 right. How many percentage points more accurate is Model A?
Answer key
- collect fruit photos
- label each example
- 50
- to see if it learned
- 4
- set aside test photos
- label each example
- paper and examples
- more labelled examples
- 16
- tag each photo by type
- 5
- 5
- pick a question to solve
- try unseen examples
- 18
- correct ÷ total × 100
- 56
- collect fruit photos
- 5
- train the model
- 10
- test on new photos
- 14
- 72
- label each example
- correct bad labels
- 36
- 60
- 10
- 32
- 50
- calculate percent right
- 104
- let it learn patterns
- 10
- 8
- 48
- 8
- 5
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students