Real Time Smart Career Path Advisor: An AI Driven, Microservice Oriented Platform for Adaptive Learning Based on Industry Trends
Keywords:
Microservices, Architecture, Machine Learning, Natural Language, Processing (NLP), Industry Trend, Analysis Real Time, CareerAbstract
This study presents the Smart Career Path Advisor, an intelligent platform designed to help Indonesian undergraduates and recent graduates identify optimal career paths aligned with their interests, talents, and current industry trends. Implemented on a Kubernetes‑managed microservices architecture, the system integrates five core modules: (1) User Profile, which collects demographic data, interests, and strengths; (2) Industry Trend Aggregator, which employs Scrapy and BeautifulSoup to harvest job postings from JobStreet, LinkedIn, and local portals and extract in‑demand skills such as ReactJS, Node.js, and Express; (3) Career Recommendation Engine, featuring a TensorFlow pipeline for data ingestion, preprocessing, and inference that combines collaborative filtering and NLP to deliver instant career suggestions with at least 85 % accuracy; (4) Adaptive Learning Planner, which automatically generates personalized learning paths—comprising courses, materials, and certifications—and refines content via reinforcement learning based on user feedback; and (5) Notification & Feedback, which issues real‑time updates via push notifications and email while monitoring user engagement. We evaluate the platform through usability testing with 30 students and quantitative analysis of recommendation accuracy and engagement metrics. The Smart Career Path Advisor not only provides precise, up‑to‑date career insights but also equips users with actionable learning strategies to meet the demands of the modern job market.
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