Module 1 — Start here
AI Fundamentals
AI Fundamentals
for every engineering discipline.
Even if you never become a Machine Learning engineer, AI literacy is different from AI specialization — and it's an essential part of any modern engineering career. 34 questions, six parts, no ML background assumed.
Why this matters
An engineer may use AI for:
DesignSimulationOptimization
PredictionFault diagnosisAutomation
Image inspectionNatural-language interactionData analysis
DocumentationDecision supportDigital twins
RoboticsProcess controlSafety monitoring
Energy optimization
That distinction — literacy vs. specialization — is what this module is built around. It's organized into six parts, from what AI/ML/LLMs actually are, through data and models, generative AI, deployment, and finally how to apply and verify AI in real engineering work.
01 — The reference
All 34 questions, in order
Grouped into the six parts below. Click any question to expand its answer.
02 — Self-assessment
Test what you've learned
Ten random questions pulled from a bank of 14 each round. No account, nothing sent anywhere — it all runs in this page, and your best score is remembered on this device.
Next
Once the fundamentals feel solid, Module 2 — How AI Works walks through exactly what happens between typing a prompt and getting an answer: tokenization, embeddings, attention, and generation.