Healthcare Data Science Portfolio

For my portfolio, I want to develop a complete Python data-science walkthrough based on a public healthcare dataset. The work should start with careful data cleaning (handling missing values, outliers, type conversions) and move through exploratory analysis before arriving at polished visual insights created with pandas, NumPy and Matplotlib. After the EDA, I would like you to implement at least one simple machine-learning model that suits the data—classification, regression or clustering—so feel free to choose whichever fits best once you have explored the variables and target. Please keep the modelling lightweight and well-commented so another student can easily follow the logic. Deliverables • Jupyter notebook (.ipynb) containing all code, visualisations and narrative explanations • Cleaned CSV (or similar) ready for analysis • Brief README summarising the dataset source, project steps and results Acceptance criteria • Notebook runs end-to-end without errors in a fresh environment (Python 3.x) • Visualisations clearly illustrate at least three key insights from the data • Model performance is reported with appropriate metrics and interpreted in plain language The goal is a portfolio-ready project that demonstrates solid data-science technique while remaining accessible to fellow students.