Impact Factor
Call For Paper
Volume 12 Issue 07
July 2026
Author(s)
Abstract
In The Current Competitive Job Market, Students And Professionals Face Significant Challenges In Planning And Tracking Their Career Development Effectively. The Absence Of Personalized Guidance And Real-time Progress Monitoring Often Leads To Inefficient Skill Development And Delayed Career Readiness. This Paper Proposes CareerPathAI, An Intelligent System That Combines Machine Learning Models With Multi-platform Integration To Generate Personalized Career Roadmaps And Track Skill Development. The System Integrates Data From GitHub And LeetCode Platforms Using REST APIs And Applies Random Forest And Logistic Regression Algorithms To Assess Career Readiness. The Hybrid Approach Captures Both Technical Proficiency Metrics And Learning Patterns To Provide Accurate Readiness Scores. CareerPathAI Demonstrates Superior Performance In Career Path Personalization And Progress Assessment, Offering Students Clear Direction And Measurable Growth Indicators For Their Professional Development.
Keywords
Paper ID
IJSARTV11I10104174
Publication Date
October 24, 2025
Research Area
Computer Science And Engineering