This capstone was one of my proudest projects, not because it went perfectly, but because it taught me so much through feedback, mistakes, and revision. Over the semester, I worked through the full process of building a data science project, from choosing a research question to cleaning data, building models, evaluating results, and creating a final report. This post is a behind-the-scenes reflection on what I built, what I struggled with, and what I learned along the way. In this post: - Why This Capstone Mattered - Choosing the Topic: From Interest to Research Question - Data Cleaning Process - Building the Models - Learning How to Evaluate Results - Turning Assignments into a Final Report - Final Reflection: What I Learned Why This Capstone Mattered In my final capstone for my data science bachelor’s degree, I researched the connection between pre-existing conditions, simple demographic...