Lesson 2.1 · From Data to Predictions
Translate the training process into plain steps so you know what’s happening behind the scenes.
Prompt Recipe: Training Story
Describe how a machine learning model is trained using the analogy of teaching a student with flashcards. Keep it to 120 words.Lesson 2.2 · Bias & Gaps
Bias isn’t just a buzzword—it affects how reliable your outputs are.
Prompt Recipe: Bias Checklist
You’re an ethics coach. List a quick checklist I should run whenever I use AI to analyze or generate content to avoid biased or harmful outputs.Try This Twist
Ask the AI to apply the checklist to one of your own prompts or projects. Do the risks feel realistic?
Lesson 2.3 · Model Critique Practice
You’ll give the AI a fictional dataset and let it critique what could go wrong.
Prompt Recipe: Fake Dataset
I have a dataset of job applicants with columns (Name, Gender, University, GPA, Interview Score, Hire Decision). Critique this dataset: what information might be missing, and where could bias appear? Suggest 3 questions I should ask before trusting it.Reflect & Apply
What extra data would make the analysis fairer? Write it down for future projects.