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 — pick a question to solve or split train and test? (a) pick a question to solve (b) split train and test
- 2.🧪 You can plan a simple AI project with… (a) nothing at all (b) only a big robot (c) paper and examples (d) a secret password
- 3.❌ Saanvi’s leaf identifier was tested on 15 new leaf photos and got 14 right. How many did it get wrong?
- 4.📋 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
- 5.📋 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
- 6.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 6 right and Model B got 5 right. How many percentage points more accurate is Model A?
- 7.🧪 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
- 8.📦 Saanvi collected 70 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
- 9.🧪 What is accuracy? (a) total − correct (b) correct + total (c) correct ÷ total × 100 (d) total × 2
- 10.🎯 Aarav’s leaf identifier was tested on 5 new leaf photos and got 5 right. What is its accuracy in percent?
- 11.🎯 Tara’s fruit sorter is 80% accurate. If it is tested on 10 new fruit photos, how many should it get right?
- 12.📋 Planning an AI project: which comes first — split train and test or let it learn patterns? (a) split train and test (b) let it learn patterns
- 13.📋 Planning an AI project: which comes first — improve data, retest or test on new photos? (a) improve data, retest (b) test on new photos
- 14.🎯 Meera’s fruit sorter was tested on 50 new fruit photos and got 42 right. What is its accuracy in percent?
- 15.❌ Kabir’s recycling sorter was tested on 37 new waste photos and got 36 right. How many did it get wrong?
- 16.🎯 Tara’s handwriting reader was tested on 5 new handwritten letters and got 4 right. What is its accuracy in percent?
- 17.🎯 Aarav’s handwriting reader was tested on 5 new handwritten letters and got 4 right. What is its accuracy in percent?
- 18.🎯 Saanvi’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
- 19.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 20 right and Model B got 19 right. How many percentage points more accurate is Model A?
- 20.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 23 right and Model B got 14 right. How many percentage points more accurate is Model A?
- 21.📦 Saanvi collected 50 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
- 22.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 19 right and Model B got 16 right. How many percentage points more accurate is Model A?
- 23.🎯 Rohan’s recycling sorter is 80% accurate. If it is tested on 40 new waste photos, how many should it get right?
- 24.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 8 right and Model B got 5 right. How many percentage points more accurate is Model A?
- 25.📋 Planning an AI project: which comes first — split train and test or fix it and test again? (a) split train and test (b) fix it and test again
- 26.❌ Saanvi’s leaf identifier was tested on 29 new leaf photos and got 22 right. How many did it get wrong?
- 27.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it faster (c) to make it bigger (d) to see if it learned
- 28.📋 Planning an AI project: which comes first — correct bad labels or label each example? (a) correct bad labels (b) label each example
- 29.📋 Planning an AI project: which comes first — set aside test photos or improve data, retest? (a) set aside test photos (b) improve data, retest
- 30.🎯 Meera’s handwriting reader is 50% accurate. If it is tested on 10 new handwritten letters, how many should it get right?
- 31.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 16 right and Model B got 12 right. How many percentage points more accurate is Model A?
- 32.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
- 33.🎯 Ishaan’s bird-song app was tested on 20 new bird songs and got 10 right. What is its accuracy in percent?
- 34.📋 Planning an AI project: which comes first — recheck every label or work out the accuracy? (a) recheck every label (b) work out the accuracy
- 35.🎯 Ananya’s recycling sorter was tested on 25 new waste photos and got 20 right. What is its accuracy in percent?
- 36.🎯 Meera’s bird-song app is 80% accurate. If it is tested on 80 new bird songs, how many should it get right?
- 37.🎯 Aarav’s handwriting reader is 50% accurate. If it is tested on 90 new handwritten letters, how many should it get right?
- 38.❌ Aarav’s handwriting reader was tested on 43 new handwritten letters and got 39 right. How many did it get wrong?
- 39.📋 Planning an AI project: which comes first — work out the accuracy or let it learn patterns? (a) work out the accuracy (b) let it learn patterns
- 40.📋 Planning an AI project: which comes first — set aside test photos or recheck every label? (a) set aside test photos (b) recheck every label
Answer key
- pick a question to solve
- paper and examples
- 1
- let it learn patterns
- tag each photo by type
- 10
- more labelled examples
- 56
- correct ÷ total × 100
- 100
- 8
- split train and test
- test on new photos
- 84
- 1
- 80
- 80
- 100
- 4
- 36
- 40
- 15
- 32
- 30
- split train and test
- 7
- to see if it learned
- label each example
- set aside test photos
- 5
- 20
- 10
- 50
- recheck every label
- 80
- 64
- 45
- 4
- let it learn patterns
- recheck every label
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students