Development of an Intelligent System for Matching University Curricula with Labor Market Requirements and Creating an Educational Roadmap

This paper presents the design and experimental evaluation of an intelligent system that compares university curricula with labor market requirements to identify skill gaps and generate personalized educational roadmaps for students. The proposed framework integrates data from academic course catalogs and job postings using Natural Language Processing (NLP) and semantic similarity models. Quantitative analysis across IT disciplines (2023–2025) reveals significant disparities in skills related to Cloud Computing, DevOps, and Cybersecurity. Visualization of data using bar charts, temporal trends, and heatmaps provides an empirical foundation for aligning higher education with evolving industry needs. The developed system serves as both an analytical and advisory tool, supporting curriculum modernization and personalized student guidance.