Upload course_recommendations dataset

README.md

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+---
+license: mit
+task_categories:
+- tabular-regression
+- tabular-classification
+tags:
+- nigeria
+- education
+- africa
+- synthetic-data
+- course-recommendations
+language:
+- en
+size_categories:
+- 100K<n<1M
+pretty_name: Nigeria Education - Course Recommendations
+---
+
+# Nigeria - Course Recommendations
+
+## Dataset Description
+
+AI-generated course recommendations with confidence scores and reasons.
+
+## Dataset Information
+
+- **Country**: Nigeria
+- **Dataset Name**: course_recommendations
+- **Total Records**: 100,000
+- **Total Columns**: 8
+- **File Size**: 1.47 MB
+- **Format**: Parquet (full data), CSV (sample)
+- **Generated**: 2025-10-21T23:15:54.764202
+
+## Schema
+
+| Column | Data Type | Description |
+|--------|-----------|-------------|
+| `recommendation_id` | object | Recommendation Id |
+| `student_id` | object | Student Id |
+| `recommended_course` | object | Recommended Course |
+| `recommendation_reason` | object | Recommendation Reason |
+| `confidence_score` | float64 | Confidence Score |
+| `status` | object | Status |
+| `recommendation_date` | datetime64[ns] | Recommendation Date |
+| `country` | object | Country |
+
+## Sample Data
+
+The dataset includes a 10,000-row sample in CSV format for quick exploration.
+
+## Data Quality
+
+- **Validation Status**: ✅ Passed
+- **Missing Data**: ~2-5% (realistic pattern)
+- **Data Type Enforcement**: Strict
+- **Cross-Dataset Consistency**: Maintained
+
+## Dependencies
+
+- `student_profiles`
+- `assessment_scores`
+
+## Usage Example
+
+### Python (Pandas)
+```python
+import pandas as pd
+
+# Load full dataset
+df = pd.read_parquet('course_recommendations_full.parquet')
+print(f"Loaded {len(df):,} records")
+print(df.head())
+
+# Load sample
+df_sample = pd.read_csv('course_recommendations_sample.csv')
+print(df_sample.describe())
+```
+
+### Python (Hugging Face Datasets)
+```python
+from datasets import load_dataset
+
+# Load from Hugging Face
+dataset = load_dataset('nigeria-education-course_recommendations')
+df = dataset['train'].to_pandas()
+```
+
+## Data Generation
+
+This dataset was generated using statistical distributions based on:
+- UNICEF education statistics for Nigeria
+- World Bank development indicators
+- Nigerian Ministry of Education data
+- Realistic probability distributions
+
+**Note**: This is synthetic data generated for research and testing purposes.
+
+## Related Datasets
+
+This dataset is part of the **Nigeria Education Datasets Collection** (45 datasets total).
+
+Browse the full collection: [Nigeria Education Datasets](https://huggingface.co/collections/nigeria-education)
+
+## Citation
+
+```bibtex
+@dataset{nigeria_course_recommendations_2025,
+  title={Nigeria Education Dataset: Course Recommendations},
+  author={[Your Name/Organization]},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/nigeria-education-course_recommendations}
+}
+```
+
+## License
+
+[Specify your license]
+
+## Contact
+
+[Your contact information]
+
+---
+
+**Part of**: Nigeria Education Datasets Collection  
+**Total Datasets**: 45  
+**Country**: Nigeria 🇳🇬

course_recommendations_full.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0c2e478f97f3a6cbea9dc0421fd180e400c68e1d80b6206be8bc4a2c75bca5b9
+size 1536585

metadata.yaml

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+columns:
+- recommendation_id
+- student_id
+- recommended_course
+- recommendation_reason
+- confidence_score
+- status
+- recommendation_date
+- country
+country: Nigeria
+country_code: NGA
+dataset_name: course_recommendations
+dependencies:
+- student_profiles
+- assessment_scores
+dtypes:
+  confidence_score: float64
+  country: object
+  recommendation_date: datetime64[ns]
+  recommendation_id: object
+  recommendation_reason: object
+  recommended_course: object
+  status: object
+  student_id: object
+file_size_mb: 1.4654016494750977
+generated_at: '2025-10-21T23:15:54.764202'
+num_columns: 8
+num_rows: 100000
+validation:
+  checks: {}
+  passed: true
+version: 1.0.0