International Journal of Computer Techniques – Volume 12 Issue 3, May – June 2025
Authors
Lakshya – Dept. of IT, NIET, Greater Noida, India.
Ayush Kumar Sharma – Dept. of IT, NIET, Greater Noida, India.
Azhad Batt – Dept. of IT, NIET, Greater Noida, India.
Gaurav Yadav – Dept. of IT, NIET, Greater Noida, India.
Dr. Ritesh Rastogi – Professor, Dept. of IT, NIET, Greater Noida, India.
Abstract
The **Smart Career Path Recommender** is an **AI-driven platform** designed to provide **personalized career guidance, skill gap analysis, and job readiness assessments** using **Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and semantic search techniques**. The system automates **resume generation, interview preparation, and career recommendations**, ensuring **efficient and targeted career support for students and professionals**.
Keywords
AI Career Guidance, Skill Gap Analysis, LLMs, Retrieval-Augmented Generation, Semantic Search, AI-Powered Resume Generator, AI-driven Job Preparation.
Conclusion
The **Smart Career Path Recommender** successfully leverages **advanced AI-driven methodologies** to provide **scalable, accessible, and adaptive career counseling**. With robust technical foundations and **real-time feedback mechanisms**, the system offers **efficient career assessment tools**, paving the way for **data-driven and personalized job readiness solutions**.
References
A. Ramesh et al. (2023). “An Intelligent Career Guidance System Using Machine Learning.” Int. Journal of Computer Applications.
R. Kumar & S. Verma (2022). “Mobile-Based Career Path Recommendation for College Students.” Journal of Emerging Educational Technologies.
S. Roy & P. Das (2022). “Skill Recommendation Framework for Career Planning.” ACM Digital Library.
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