SkillGap AI: An AI-Powered Career Guidance Platform

Author(s)	Mr. Syed Khizer, Mr. Altamash Shaikh, Mr. Syed Sadiq Ahamed, Mr. Chirag A, Prof. Dr. Anitha K
Country	India
Abstract	Career guidance remains a significant challenge for students in technical disciplines. Most existing platforms offer generic skill roadmaps without considering the individual’s current competency profile. This paper presents SkillGap AI, an end-to-end intelligent career guidance platform that leverages natural language processing (NLP), vector embeddings, and large language models (LLMs) to deliver a fully personalized skill gap analysis and learning roadmap. The system automatically extracts skills from a student’s uploaded resume using spaCy, computes semantic similarity between user skills and target job role requirements using sentence transformers and ChromaDB, and generates a tailored week-by-week learning roadmap using the Gemini 1.5 Flash API. The platform further incorporates an AI-driven mock interview module and project recommendation engine. Experimental evaluation demonstrates that the system achieves high precision in skill extraction and produces contextually relevant, role-specific learning plans.
Keywords	skill gap analysis, NLP, career guidance, vector embeddings, large language models, resume parsing, personalized learning
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-07
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.77353

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