built predictive models, including Naive Bayes and Decision Trees, to analyze applicant data for Teach For America. The project aimed to identify applicants most likely to complete the admissions process, tackle challenges like class imbalance, and improve recruitment strategies. Proposed actionable recommendations, including simplifying the application process, leveraging deadlines, and personalizing outreach, to optimize engagement and completions. This project demonstrated the application of data-driven decisions and collaborative problem-solving to real-world challenges in education.
Aug 01, 2024 - Nov 30, 2024