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online-course-performance-predictor
jomarie04/online-course-performance-predictor
online-course-performance-predictor is a machine learning model from jomarie04. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc0-1.0.
--- modelname: online-course-performance-predictor license: cc0-1.0 language: en tags: - tabular - classification - education - student-performance - synthetic-data metrics: - accuracy - f1 - rocauc ---
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Updated Jan 27, 2026
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At a glance
- License
- cc0-1.0
- Access
- Public
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026
- SHA
- 1c538432
Model card
From the Hugging Face model README
model_name: online-course-performance-predictor license: cc0-1.0 language: en tags:
- tabular
- classification
- education
- student-performance
- synthetic-data metrics:
- accuracy
- f1
- roc_auc
Online Course Performance Predictor
Model Overview
Online Course Performance Predictor is a machine learning model trained to predict whether a student will successfully complete an online course.
The dataset is fully synthetic, representing student engagement and learning behavior.
Intended for demos, research, and ML experimentation.
Model Details
- Model Name: online-course-performance-predictor
- Model Type: Binary Classification
- Framework: scikit-learn / XGBoost
- Input: Tabular CSV data
- Output: Completion Status (Completed / Dropped)
Training Data
Synthetic dataset with the following features:
| Feature | Type | Description |
|---|---|---|
| student_id | String | Unique student identifier |
| age | Integer | Student age |
| gender | Categorical | Gender |
| course_category | Categorical | Data Science, ML, Web Dev, etc. |
| enrollment_date | Date | Course enrollment date |
| progress_percent | Integer | Course progress in % |
| avg_weekly_hours | Float | Avg weekly study hours |
| completion_status | Binary | Target label (Completed / Dropped) |
Intended Use
✅ Predicting student course completion (synthetic/demo)
✅ Educational ML tutorials
❌ Real-world academic decision-making
Evaluation Results
| Metric | Score |
|---|---|
| Accuracy | 0.87 |
| F1-score | 0.85 |
| ROC-AUC | 0.89 |
Limitations
- Synthetic data only
- Simplified student behavior
- Not representative of real-world universities
Ethical Considerations
Model does not use real student data.
Misuse in real educational decisions could create unfair outcomes.
License
This model is released under the CC0 1.0 Universal License (Public Domain).
- License
- cc0-1.0
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026