I submitted my first draft at the start of April and received quality feedback. I really mean that because this was the first course where the professor met with us one-on-one to provide feedback and discuss our project. It was very valuable and I am grateful for Dr. Quintanar and her support throughout this course. I revised my work and finalized my paper, code and presentation.
My capstone experience project (M.S. Advanced Data Analytics), was an exploration and analysis of Fall 2023 U.S. college enrollment data (115K records, 5,900+ institutions) to uncover demographic patterns and predict graduate enrollment.
- Key Findings:
- Women consistently outnumber men in enrollment, with the gap widening at the graduate level (60.6% vs. 39.4%).
- Hispanic student representation drops sharply from undergrad (25.6%) to graduate (15.2%).
- Institutional size distribution is highly skewed (median 588 vs. mean 3,332).
- **Models Utilized: Linear Regression, Decision Trees, and Random Forest.
- Best performer: Random Forest (R² ≈ 0.78, MAE ~631).
- Strongest predictors of graduate enrollment: female enrollment and Asian student representation.