BitWithBite
AI & Machine Learning Worksheet
🤖 Careers in AI & ML
SCORE___ / 20
NameClassDate
After this worksheet you can
Know the main AI/ML rolesSkills per roleTypical pipelines of workHow to start building proof📚 Quick Recap
AI and ML job titles exploded in volume over the past two years, and a lot of companies slap "AI Engineer" on a job posting that's really a Machine Learning Engineer role, or vice versa. The title on the posting matters less than the actual responsibilities listed underneath it. This lesson gives you the real distinctions so you can read past the buzzwords.
🧠 Section A · Concept Check ● BEGINNER 4 × 1 = 4
1Builds/serves models in production:
2Explores data and builds insight/models:
3Maintains data pipelines/warehouses:
4Best first proof of skill:
🧮 Section B · Problem Solving ● INTERMEDIATE 2 + 3×3 = 11
5Core language for ML work: .
6Data build and clean the pipelines models depend on.
7Match role to task: deploy model API; clean TB of logs; A/B analysis.
8Three portfolio project ideas?
9Why do employers value projects over certificates?
🚀 Section C · Challenge ● CHALLENGE 5
10What is MLOps in one line?
💭 Reflection — the most useful thing I learned:
A ___/4 B ___/11 C ___/5 Total ___/20
Teacher's Signature
Parent's Signature
✂ answer key — fold or cut before handing out
1-A 2-A 3-A 4-A | 5 Python 6 engineers 7 = ML engineer; data engineer; data scientist 8 = Prediction app, dataset analysis writeup, fine-tuned model demo 9 = They show real applied ability end-to-end | 10 = DevOps for models - versioning, deployment, monitoring