This project was developed as part of the IBM SkillsBuild Internship conducted by Edunet Foundation in collaboration with AICTE.
The objective of this project is to automate the prediction of the appropriate National Social Assistance Programme (NSAP) scheme for applicants using Machine Learning.
The system helps reduce manual verification efforts, improve decision-making, and enhance the efficiency of welfare scheme allocation.
The National Social Assistance Programme (NSAP) provides financial assistance to:
- Elderly citizens
- Widows
- Persons with disabilities
Traditional verification and scheme allocation processes are often manual, time-consuming, and prone to errors.
This project aims to automate the prediction of the correct NSAP scheme based on applicant information using Machine Learning.
A Machine Learning classification model was developed using IBM Watsonx.ai AutoAI to predict the most suitable NSAP scheme.
- IGNOAPS (Old Age Pension Scheme)
- IGNWPS (Widow Pension Scheme)
- IGNDPS (Disability Pension Scheme)
- IBM Cloud Lite
- IBM Watsonx.ai Studio
- IBM AutoAI
- IBM Watson Machine Learning
- Machine Learning
- Data Analytics
- AIKosh Dataset
Source: AIKosh NSAP Dataset
The dataset contains demographic and socio-economic attributes used to train and evaluate the Machine Learning model.
- Dataset Collection
- Data Upload to IBM Watsonx.ai
- AutoAI Model Training
- Pipeline Generation
- Best Model Selection
- Model Deployment
- Prediction using IBM Cloud
- AutoAI Generated Pipelines: 9
- Best Model: LGBMClassifier
- Deployment Platform: IBM Watson Machine Learning
- Prediction Interface: IBM Cloud Deployment UI
- Successfully automated NSAP scheme prediction.
- Achieved high prediction accuracy.
- Reduced manual verification efforts.
- Demonstrated end-to-end Machine Learning deployment using IBM Cloud services.
- Generated real-time predictions through deployed cloud models.
- Integration with Government Service Portals
- Mobile Application Development
- Web-Based Prediction System
- Serverless API Deployment
- Enhanced Dataset Integration
- Improved model performance using larger datasets
Program: IBM SkillsBuild Internship on AI & Cloud Technologies
Organization: Edunet Foundation in collaboration with IBM SkillsBuild and AICTE
Duration: 15 July 2025 – 07 August 2025
Bettam Anand
B.Tech – Computer Science & Engineering (Data Science)
JNTUH University College of Engineering Palair
- LinkedIn: https://www.linkedin.com/in/bettam-anand/
- GitHub: https://github.com/Anand1522
This project is intended for educational and research purposes only.