Scrumlord : AI-Driven Internship Management System

Overview

The AI-Driven Internship Management System (AIDIMAS) is a comprehensive platform designed to bridge the gap between students, colleges, and companies by providing a simulated, real-world internship experience. The system leverages AI to manage projects, track progress, and provide actionable feedback, ensuring students gain practical skills that align with industry expectations.

Key Features

1. AI as Project Manager: Assigns, monitors, and reviews tasks daily, simulating real-world projects with sprints, deadlines, and feedback.
2. GitHub Integration: Tracks commits, pull requests, and code quality, providing instant AI feedback to improve skills.
3. Real-World Simulations: Students work on industry-like projects sourced from company requirements or datasets.
4. Dynamic Learning Modules: Replaces "tutorial hell" with task-specific, on-the-spot learning resources.
5. Performance Analytics: Dashboards with metrics like task completion rates, growth, and code quality.
6. Industry Collaboration: Companies access anonymous performance data to identify skilled candidates.
7. Certification: Verifiable certificates with detailed performance metrics.

Benefits

• For Students: Hands-on, real-world experience.
• For Companies: Pre-trained, industry-ready candidates.
• For Colleges: Bridges skill gaps without additional infrastructure.

User Stories

1. User Onboarding

• Student: Sign up and create a profile to begin the AI-driven internship experience.
• Company: Create a profile and upload project requirements for AI simulation.
• College/School: Create an institution profile to enroll multiple students and monitor their progress.
• Admin: Manage user accounts and validate registrations.

2. AI Project Assignment

• Student: Receive AI-assigned tasks daily based on skill level.
• AI System: Track project progress and reassign tasks dynamically.
• College/School: Assign specific project types to students based on curriculum and interests.

3. GitHub Integration

• Student: Track GitHub contributions automatically.
• AI System: Analyze code quality and provide actionable feedback.
• College/School: Monitor all enrolled students’ GitHub activities.

4. Real-World Simulations

• Student: Work on simulated projects with deadlines and sprints.
• Company: Provide realistic projects aligning with industry needs.
• College/School: View and approve project templates.

5. Dynamic Learning Modules

• Student: Access on-demand learning resources tailored to tasks.
• AI System: Deliver just-in-time learning modules when students struggle.
• College/School: Integrate custom learning materials into the AI system.

6. Performance Analytics

• Student: View detailed metrics (task completion, skill growth, code quality).
• Mentor/Admin: Access analytics to monitor performance and identify top candidates.
• College/School: Access collective analytics for all enrolled students.

7. Certification

• Student: Receive detailed, verifiable certificates upon project completion.
• College/School: Issue co-branded certificates to students.

8. Industry Collaboration

• Company: Access anonymized performance data to identify skilled candidates.
• Student: Reflect performance in industry-standard metrics.
• College/School: Connect with companies to secure internship opportunities.

9. Monetization and Subscription

• College/School: Subscribe to provide students access to practical, AI-managed internships.
• Student: Access freemium features to explore the platform.
• Company: Pay for specific services like accessing top candidates or providing project templates.

10. Admin Control

• Admin: Manage projects, users, and system configurations.
• Admin: Track system performance and resolve issues.
• Admin: Manage different subscription tiers for colleges, students, and companies.

Architecture Design Documentation

1. High-Level System Architecture Diagram

The system architecture includes:

• Frontend (Next.js): Displays project and task management interfaces.
• API Layer (Next.js): Handles backend logic and AI integration.
• AI Engine (LLM APIs + TensorFlow): Manages tasks, provides feedback, and adapts learning modules.
• Database (PostgreSQL): Stores user, project, and task data.
• GitHub Integration Service: Tracks student activity on GitHub.
• External Services (LLM APIs, Cloud Storage): Integrates with external APIs and cloud services.

2. Components Breakdown

• Frontend (Next.js): Built with Next.js and React.js for rendering UI and handling routing.
• Backend (API Layer in Next.js): Manages authentication, API requests, and interfaces with AI and GitHub services.
• AI Engine (LLM APIs + TensorFlow): Handles task management, performance feedback, and adaptive learning.
• GitHub Integration Service: Fetches and monitors GitHub activity.
• Database (PostgreSQL): Stores all user, project, and performance data.
• External Services: Integrates with LLM APIs, cloud services, and email/notification systems.

3. Data Flow and Interaction

• User Flow: Students sign up, receive tasks, and get feedback. Colleges and companies monitor progress.
• GitHub Integration Flow: Tracks student activity and feeds data into the backend.
• AI Feedback Flow: Evaluates performance and provides dynamic feedback.

Getting Started

To get started with AIDIMAS, follow these steps:

1. Clone the repository.
2. Install dependencies using npm install.
3. Set up the PostgreSQL database and configure the environment variables.
4. Run the application using npm run dev.