🧭 PathGuide AI

Career Guidance & Tamil Nadu Government Exam Preparation Platform

Navigate Your Future. Discover Your Path. Achieve Your Goals.

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🌟 Overview

PathGuide AI is an intelligent, bilingual career and government examination guidance platform designed especially for students and aspirants in Tamil Nadu.

The platform combines Career Path Guidance and Tamil Nadu Government Exam Preparation into a single application, helping users make informed decisions through personalized recommendations, Machine Learning-assisted predictions, and structured study plans.

With its English and Tamil interface, PathGuide makes career exploration and government exam preparation more accessible, organized, and user-friendly.

🎯 Two Intelligent Guidance Paths

🎓 College Career Path	🏛️ Tamil Nadu Government Exams
Degree-based career exploration	Government examination guidance
Department and domain selection	TNPSC and TNUSRB preparation
Personalized career recommendations	Exam preparation strategies
Skill development roadmap	Structured study plans
Courses and project suggestions	Success-score estimation
Internship and salary insights	Physical fitness eligibility

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✨ Core Features

🎓 1. Career Guidance System

An intelligent career guidance module that helps students discover suitable career opportunities based on their educational background and professional interests.

• Dynamic selection: Degree → Department → Domain → Role.
• Career recommendations from a dataset of 1,000 roles.
• Personalized career roadmap.
• Required skills and technology recommendations.
• Course, project and internship suggestions.
• Salary information for selected roles.
• Location-based career guidance.
• Weekly study planning and progress tracking.

🏛️ 2. Tamil Nadu Government Exam Guidance

A dedicated preparation system for students aspiring to enter Tamil Nadu government services.

• TNPSC and TNUSRB examination guidance.
• Qualification-based exam selection.
• Exam preparation duration and study availability inputs.
• Structured examination preparation strategies.
• Success-score estimation.
• Physical fitness and BMI evaluation for applicable uniformed services.
• Personalized preparation recommendations.

🤖 3. Machine Learning & Intelligence

PathGuide incorporates Machine Learning and rule-based recommendation techniques to support personalized guidance.

Component	Purpose
Random Forest Predictor	ML-assisted success estimation
Recommendation Engine	Personalized learning recommendations
Daily Plan Generator	Daily preparation tasks
Fitness Checker	BMI and physical eligibility evaluation
Rule-Based Logic	Converts user inputs into actionable guidance

📅 4. Smart Study Planning

• Personalized preparation roadmaps.
• Weekly study schedules.
• Daily learning activities.
• Study-hour-based planning.
• Preparation-duration-based recommendations.
• Skill development and learning suggestions.

🌐 5. Bilingual User Experience

• English and Tamil language support.
• Dynamic language switching.
• User-friendly navigation.
• Responsive interface for desktop, tablet and mobile.
• Modern interface with consistent visual branding.
• Light and dark themes in the admin dashboard.

🔐 6. Admin Management System

A protected administration interface for managing platform operations.

• Secure admin authentication.
• Failed login attempt tracking.
• Account lockout mechanism.
• Session inactivity timeout.
• Feature activation and deactivation.
• Welcome banner management.
• Report and audit-log exports.
• Backup management.
• Administrative configuration.

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🧠 Machine Learning Architecture

PathGuide combines predictive intelligence with rule-based planning to generate actionable recommendations.

ML Components

1. Success Prediction

• Uses a Random Forest-based prediction approach.
• Processes relevant preparation inputs.
• Generates a success-oriented estimate.

2. Recommendation Engine

• Analyzes user selections and preparation requirements.
• Generates personalized learning recommendations.
• Supports career and examination planning.

3. Daily Plan Generator

• Converts preparation requirements into daily activities.
• Organizes learning tasks based on available study time.

4. Fitness Checker

• Calculates BMI.
• Evaluates applicable physical eligibility criteria.
• Provides fitness-related guidance.

Implementation note: The predictor, recommendation and related ML modules are present in the codebase. The current running application uses career data and generator modules directly; the complete ML pipeline and database models are still being integrated.

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🏗️ System Architecture

PathGuide follows a modular web application architecture with a Flask backend, frontend templates, data modules and Machine Learning components.

flowchart TB
    U["PathGuide Users"]

    U --> D["Main Dashboard"]

    D --> C["Career Guidance"]
    D --> E["Government Exam Guidance"]

    C --> CI["Career Input"]
    E --> EI["Exam Input"]

    CI --> B["Flask Backend"]
    EI --> B

    B --> DATA["Career & Exam Data"]
    B --> ML["ML Prediction"]
    B --> RE["Recommendation Engine"]
    B --> SP["Study Plan Generator"]
    B --> FC["Fitness Checker"]

    DATA --> OUT["Personalized Output"]
    ML --> OUT
    RE --> OUT
    SP --> OUT
    FC --> OUT

    OUT --> R["Career / Exam Results"]

    A["Admin Panel"] --> SEC["Authentication & Security"]
    SEC --> M["Platform Management"]

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Application Workflow

flowchart LR
    A["User Dashboard"] --> B{"Select Guidance"}
    B --> C["Career Path"]
    B --> D["TN Government Exams"]

    C --> E["Career Profile"]
    D --> F["Exam Details"]

    E --> G["Backend Processing"]
    F --> G

    G --> H["ML & Rule-Based Logic"]
    H --> I["Recommendations"]
    I --> J["Personalized Results"]
    J --> K["Study Plan & Roadmap"]

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🧰 Technology Stack

Layer	Technologies
Programming Language	Python 3.8+
Backend Framework	Flask 2.3
Frontend	HTML5, CSS3, JavaScript
Template Engine	Jinja2
Machine Learning	scikit-learn
ML Algorithm	Random Forest
Data Processing	NumPy, Pandas
Model Management	Joblib
Data Sources	Python modules, CSV datasets
Database Layer	Database models and initialization scripts
Version Control	Git, GitHub
Development Environment	Visual Studio Code

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📁 Project Structure

PathGuide/
│
├── README.md
├── index.html
├── requirements.txt
│
└── Code/
    │
    ├── app.py
    ├── requirements.txt
    ├── .env.example
    │
    ├── backend/
    │   ├── app.py
    │   ├── career_output_generator.py
    │   ├── config.py
    │   ├── init_db.py
    │   │
    │   ├── ml/
    │   │   ├── success_predictor.py
    │   │   ├── recommendation_engine.py
    │   │   ├── daily_plan_generator.py
    │   │   └── fitness_checker.py
    │   │
    │   ├── models/
    │   │   ├── career.py
    │   │   └── exam.py
    │   │
    │   └── utils/
    │
    ├── data/
    │   ├── career_data.py
    │   ├── role_content.py
    │   └── Career Path Roles.csv
    │
    ├── frontend/
    │   ├── templates/
    │   │   ├── index.html
    │   │   ├── career_input.html
    │   │   ├── career_output.html
    │   │   ├── exam_input.html
    │   │   ├── exam_output.html
    │   │   └── partials/
    │   │
    │   └── static/
    │       ├── css/
    │       ├── js/
    │       └── img/
    │
    ├── docs/
    │   ├── PROJECT_SUMMARY.md
    │   ├── ARCHITECTURE.py
    │   └── QUICKSTART.md
    │
    └── scripts/
        ├── run.ps1
        └── verify_setup.ps1

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⚙️ Getting Started

Prerequisites

• Python 3.8 or newer
• Git
• Visual Studio Code

1. Clone the Repository

git clone https://github.com/suvinbrettleeroy/PathuGuide-AI.git

cd PathuGuide-AI

2. Navigate to the Code Directory

cd Code

3. Create a Virtual Environment

python -m venv venv

4. Activate the Environment

.\venv\Scripts\Activate.ps1

5. Install Dependencies

pip install -r requirements.txt

6. Configure Environment Variables

Copy .env.example to .env and configure the required application settings and secure admin credentials.

7. Run the Application

python app.py

For Render deployment, use this start command from the repository root:

gunicorn pathguide.app

8. Open in Browser

http://127.0.0.1:5000

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🔗 Application Routes

Route	Description
/	Main dashboard
/career/input	Career guidance input
/career/output	Personalized career results
/exam/input	Government exam input
/exam/output	Exam preparation results
/admin-login	Admin authentication
/admin	Admin dashboard
/api/career/*	Career selection and progress APIs

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📊 Development Status

Module	Status
Main Dashboard	Implemented
Career Guidance	Implemented
Government Exam Guidance	Implemented
English & Tamil Support	Implemented
Flask Backend	Implemented
Career Recommendation Logic	Implemented
Career Data Integration	Implemented
Admin Authentication	Implemented
Admin Management	Implemented
Random Forest Predictor	Codebase implementation; integration in progress
Recommendation Engine	Codebase implementation
Daily Plan Generator	Codebase implementation
Fitness Checker	Codebase implementation
Complete Database Integration	In progress

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🔮 Future Enhancements

• Advanced ML prediction and model evaluation.
• Improved recommendation explainability.
• Expanded career and examination datasets.
• Advanced learning analytics dashboard.
• User profile and long-term progress tracking.
• Persistent database integration.
• AI-powered conversational career assistant.
• Real-time examination notifications.
• Resume analysis and skill-gap identification.
• Mobile application integration.

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👥 Team Members

Team Member	Responsibilities
Suvin Brettlee Roy B.	Team Lead, System Architecture, Frontend, Backend, UI/UX and Integration
Duraimurugan K.	Data Collection, Data Processing, ML and Recommendation Development
Brian Benton Nelson P.	Testing, Debugging, Output Validation and Documentation

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🎯 Project Objectives

• Integrate career guidance and government exam preparation into one platform.
• Provide personalized recommendations based on individual user profiles.
• Implement ML-assisted prediction and intelligent guidance.
• Generate structured daily and weekly study plans.
• Improve accessibility through English and Tamil language support.
• Provide secure administration and efficient platform management.

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👨‍💻 Developer

Suvin Brettlee Roy B.

B.Tech – Computer Science and Engineering
Artificial Intelligence & Machine Learning

Technical Interests:
Artificial Intelligence · Machine Learning · Full-Stack Development · Data Science · Generative AI · AI Agents · Automation

GitHub Profile

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🙏 Acknowledgments

• Tamil Nadu Public Service Commission (TNPSC)
• Tamil Nadu Uniformed Services Recruitment Board (TNUSRB)
• Flask and Python communities
• Open-source Machine Learning community

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🧭 PATHGUIDE AI
Career Path and Tamil Nadu Government Exam Path

Navigate Your Future.

⭐ If you find this project interesting, consider starring the repository!

_{Built with ❤️ using Python, Flask and Machine Learning.
© 2026 PathGuide AI · Educational Project}