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@article{200325,
        author = {Prapti Manoj Kore and Supriya mali},
        title = {SkillBridge: An AI-Powered Web Application for Skill Gap Analysis and Personalised Learning Path Generation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {2528-2531},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200325},
        abstract = {The rapid evolution of the technology industry continuously widens the gap between the skills possessed by students and early-career professionals and those demanded by the job market. Traditional career guidance methods are expensive, generic, and unable to provide real-time, personalised recommendations. This paper presents SkillBridge, a full-stack web application developed using Python Flask and the Anthropic Claude large language model (LLM) API. The system accepts a user's current skill set and desired job role as input and performs an intelligent, context-aware gap analysis, generating a structured 8-week, week-by-week learning roadmap with curated free resources. The application incorporates secure user authentication, persistent SQLite database storage, and a responsive dark-mode user interface built with Jinja2 templates. Experimental results demonstrate that the AI-generated roadmaps are coherent, role-specific, and practically actionable. SkillBridge provides a scalable, cost-free alternative to professional career counselling and serves as a practical proof-of-concept for AI-driven educational technology applications.},
        keywords = {Skill Gap Analysis; Large Language Models; Flask; Career Guidance; AI in Education; Learning Path Generation; Anthropic Claude API; Web Application.},
        month = {May},
        }