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Business school recommendation service

AI model increased graduate management education program enrollment by 19%.

Client

A nonprofit organization dedicated to facilitating connections between candidates interested in graduate management education and degree programs globally.

Objective

The client aimed to develop an AI model to help candidates interested in graduate management education navigate the space of business education providers and get research-based recommendations.

Solution

Data Analysis and Preparation

We started by collecting and analyzing data from both students and schools. The student dataset included demographics, academic performance, interests, and location, while the school dataset comprised academic programs, facilities, and various other performance metrics. Using exploratory data analysis (EDA), we identified patterns and cleaned the data, handling missing values, encoding categorical variables, and assigning compatibility scores.

Feature Engineering

Key features were engineered to enhance predictive power:

  • Distance to School: Calculated using the Haversine formula to assess commute feasibility.
  • Academic Fit: Compatibility score based on student grades and school admission criteria.
  • School Performance: Included graduation rates and test scores to measure school quality.
  • Student Preferences: Transformed survey data on preferences into quantifiable features.

Model Selection and Training

We selected a supervised learning approach and tested several algorithms, including logistic regression, decision trees, random forests, and gradient boosting machines (GBM). The model was trained using a labeled dataset of historical matches and optimized through grid search for hyperparameters.

Evaluation and Fine-Tuning

The model’s performance was evaluated using precision, recall, and F1-score, with k-fold cross-validation ensuring consistency. We also conducted fairness evaluations to ensure equitable recommendations across demographics. The model was iteratively fine-tuned based on these evaluations.

Result

Achievion’s AI-driven solution streamlined the process of selecting business schools, providing candidates with tailored recommendations based on minimal data inputs. The refined AI model significantly expedited the candidate selection process, enhancing efficiency by 42%.

rev
We felt that Achievion Solutions listened well to our needs and was supportive and collaborative during this process.
Nonprofit organization
Director of Research & Data Science

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