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Student Success Prediction

Nov 2024 - Dec 2024
Predictive Analytics / Feature Engineering
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Project Type

  • Association: University of Missouri-Kansas City
  • Role: Data Analytics / Predictive Modeling
  • Focus: Student performance and success drivers
  • Approach: Interpretable modeling and exploratory analysis

Objective

Identified factors influencing student success using exploratory analysis, feature engineering, and interpretable predictive modeling.

Tools & Technologies

PythonData AnalysisFeature EngineeringExploratory Data AnalysisPredictive ModelingModel Evaluation

Project Details

Analyzed academic backgrounds of parents and students along with assessment data to identify patterns associated with student performance outcomes.

Performed data preprocessing, feature engineering, and exploratory analysis to understand correlations between engagement, coursework, and student outcomes.

Built and evaluated predictive models to assess performance drivers and trade-offs, focusing on interpretability rather than only raw accuracy.

Translated analytical findings into clear insights that could support early intervention and academic planning decisions.

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