AI-Based Job Skill Gap Analyzer

Overview

An advanced AI-powered EdTech platform that evaluates a student’s technical and soft skills against current industry requirements, identifies gaps, and recommends targeted, personalized learning paths. Designed to bridge the gap between academic learning and real-world job market needs.

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Key Features

1. Automated Skill Extraction

• Leverages spaCy and BERT to accurately extract skills from LinkedIn, GitHub profiles, and uploaded resumes.

2. Industry Demand Analysis

• Aggregates and analyzes job postings (scraped from LinkedIn) to identify trending skills, technologies, and emerging industry requirements.

3. Skill Gap Detection

• Compares a user’s skill set with requirements for target roles and identifies missing competencies.

4. Personalized Learning Path

• Maps missing skills to relevant online courses and training materials from Coursera, edX, Udemy, and O*NET resources.

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Technology Stack

Layer	Technologies Used
Backend	Python, FastAPI
NLP	spaCy, BERT (HuggingFace Transformers)
Data Processing	Pandas, NumPy
Web Scraping	BeautifulSoup, Selenium (LinkedIn job postings)
Database	PostgreSQL / MongoDB
Frontend	React.js / Next.js
Deployment	Docker, AWS EC2/S3

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Dataset Sources

• O*NET — Comprehensive skills and job role dataset
• LinkedIn Job Postings — Scraped using Selenium
• Sample Student Profiles — Sourced from LinkedIn, GitHub, and mock resumes

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MVP Workflow

1. Profile Upload — User provides LinkedIn, GitHub profile, or resume file.
2. Skill Extraction — NLP model parses and detects skills.
3. Industry Demand Analysis — Fetches and processes real-time job postings.
4. Gap Analysis — Compares extracted skills with job requirements.
5. Recommendation Generation — Produces a personalized learning roadmap.

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Testing & Evaluation

• Conducted with diverse student and graduate profiles.
• Achieved ~85% accuracy in skill detection and recommendation mapping.
• Continuous improvement through real-world feedback from job application outcomes.

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Future Enhancements

• Integration with LinkedIn and Coursera APIs for real-time updates.
• Interactive user dashboards with skill progress tracking.
• Multilingual NLP support for global reach.

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System Architecture

flowchart TD
    A[Profile Upload (LinkedIn / GitHub / Resume)] --> B[Skill Extraction (spaCy / BERT)]
    B --> C[Industry Demand Analysis (LinkedIn Scraper)]
    C --> D[Gap Analysis Engine]
    D --> E[Recommendation Engine]
    E --> F[Personalized Learning Path Output]

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License

Licensed under the MIT License — free to use, modify, and distribute with attribution.