LEARNING PATH DASHBOARD FOR ENHANCING SKILLS

Abstract

Choosing the right skills and learning resources has become a major challenge for students due to the rapid growth of technology and the increasing demand for industry – specific knowledge. Most learners spend considerable time searching across different platforms to identify suitable courses, certifications, and career paths. To address this problem, this paper presents an AI-Powered Learning Path Dashboard for Enhancing Skills, a webbased application that provides personalized learning guidance based on the user’s interests and career objectives. The system is developed using Python and Streamlit, while SQLite is used for managing user information. A Large Language Model (LLM) integrated through the Groq API analyzes user inputs and generates customized learning roadmaps, recommended skills, project ideas, certification suggestions, career opportunities, estimated learning duration, and AI-based learning flowcharts. The application combines these features into a single interactive dashboard, enabling learners to access all recommendations in one place. By providing structured and personalized guidance, the proposed system reduces the effort required to plan a learning journey and helps users focus on acquiring relevant skills for their desired careers. The developed application demonstrates that AI-based recommendation systems can improve learning efficiency, support informed career planning, and encourage continuous skill development. KEYWORDS: Personalized Learning, Learning Path Dashboard, Skill Enhancement, Career Guidance, Large Language Model (LLM), Streamlit, Python, SQLite.