AI Career Gap Analysis

Introduction

The job market is becoming increasingly competitive, and many students and professionals struggle to understand which skills they need to land their desired roles. AI Career Gap Analysis is a MERN stack web application that helps users identify the gap between their current skill set and the skills required for their target career. By combining AI-powered analysis with role-based skill mapping, the platform provides personalized recommendations and a structured learning roadmap.

Problem Statement

Many aspiring developers spend months learning technologies without knowing whether they are focusing on the right skills. Existing career guidance platforms often provide generic advice rather than personalized feedback.

This project solves that problem by:

Analyzing a user’s current skills.
Comparing them with industry-required skills.
Identifying missing competencies.
Providing AI-generated recommendations to bridge the gap.

Features

🔐 Secure user authentication using JWT and bcrypt.
👤 User registration and login.
🤖 AI-powered career gap analysis.
📊 Skill gap identification based on the selected career role.
📚 Personalized learning recommendations.
🛣️ Structured learning roadmap.
💾 User profile and analysis history storage.
📱 Responsive and user-friendly interface.

Tech Stack

Frontend

React.js
Tailwind CSS
Axios
React Router

Backend

Node.js
Express.js
JWT Authentication
bcrypt.js

Database

MongoDB
Mongoose

AI Integration

AI API for generating personalized career recommendations and learning roadmaps.

How It Works

Users create an account and log in securely.
They enter their current skills and select their target job role.
The backend compares the provided skills with the required skills for that role.
AI analyzes the results and identifies missing skills.
The system generates personalized recommendations and a learning roadmap to help users achieve their career goals.

Challenges Faced

During development, I encountered several challenges, including integrating AI APIs, managing secure authentication with JWT, designing scalable MongoDB schemas, handling API communication between the frontend and backend, and creating a responsive user interface. These challenges helped me improve my problem-solving skills and gain practical experience in full-stack development.

Key Learnings

This project strengthened my understanding of:

MERN stack development
RESTful API design
Authentication and authorization
MongoDB schema design
AI integration in web applications
State management and frontend-backend communication
Error handling and debugging

Future Enhancements

Resume upload and AI resume analysis.
ATS score evaluation.
Mock interview generation.
Progress tracking dashboard.
Personalized interview questions.
Skill assessment quizzes.
Career trend analysis.
Job and internship recommendations.