Student Score Prediction Model

I’m putting together a beginner-friendly machine-learning demo that predicts student test scores. I’d like a clean, well-commented Python solution that a newcomer can open, run, and learn from without feeling overwhelmed.

Here is what I have in mind:
• A small, publicly available CSV (or a synthetic set you generate) containing study hours, attendance, or similar features, loaded with pandas.
• Exploratory analysis that highlights patterns in plain language.
• A straightforward regression pipeline—think scikit-learn’s LinearRegression or RandomForestRegressor—wrapped in a Jupyter notebook so each step is visible.
• Clear markdown explanations of why each step matters, from data split to model evaluation (R², MAE, or RMSE).
• A concise README that tells a total beginner how to recreate the environment, run the notebook, and tweak parameters.

I will judge proposals mainly on relevant past work, so please point me to any notebooks or repos that show you can explain your code well. Concise, educational, and reproducible is the entire brief; if you enjoy writing approachable tutorials, this should be quick and fun.