DBIS

In today’s rapidly evolving job market, individuals are often challenged with identifying optimal career paths and relevant educational opportunities that align with their skills, experience, and the current market demands. This thesis focuses on design and development of an Intelligent Career and Learning Pathway Recommendation System that aims to solve this issue by providing personalized career and education recommendations.

The proposed system will utilize Large Language Models (LLMs) to analyze the user’s curriculum vitae (CV) and gather additional inputs through a user-prompt interface. By collecting detailed user information, such as educational background, work experience, career goals, and real-time user prompts, the system will recommend personalized career and learning pathways. These recommendations will be aligned with emerging job market trends, industry requirements, and skill gaps as identified by real-time labor market data.

For applications please send both a CV and a transcript of records!