Career Navigator Using Machine Learning
This paper presents Career Navigator, an AI-powered career guidance system that leverages machine learning (ML) and natural language processing (NLP) to recommend personalized job roles based on user skills and interests. The system employs a Random Forest Classifier (RFC) trained on a dataset of 9,000 skill-to-job mappings (dataset9000.csv) to predict suitable careers with a confidence score. Users input their skill levels (e.g., programming, networking) via text or voice, and the system outputs detailed role descriptions, salary ranges, and interview tips. Additionally, mock tests and real-time skill assessments enhance career readiness. Built on the Django framework, Career Navigator bridges the gap between talent and opportunity, offering scalable, data-driven guidance for students, job seekers, and career changers.
Institutions
- Advanced Numerical Research and Analysis Group (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-01
- DOI
- https://doi.org/10.5281/zenodo.15104355
- Primary Topic
- Intelligent Tutoring Systems and Adaptive Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00