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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM52937
Volume:
9 |
10 |
Oct 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Students often struggle to choose the right career because they don’t have enough help or information about what’s happening in different industries. Regular ways of giving advice, like testing what you’re good at or having one-on-one chats, usually give the same type of suggestions that don’t take into account the unique skills, interests, and goals of each student. This can lead to confusion, wrong career choices, and less chance of getting a job. To solve these problems, this project introduces an AI based career advice system that offers personalized and thoughtful guidance. Using technologies like Natural Language Processing and Machine Learning, the system gathers information about a student’s grades, abilities, likes, and interests to provide tailored career options. The recommendations are updated with the latest trends in the job market, helping students make choices that are suitable for now and in the future. This system is different from traditional static advice tools because it is always available, can change with new information, and is trustworthy. It acts like a digital mentor, providing support 24/7 with automatic responses and accurate advice for students, parents, and teachers. The system is made up of three main parts: creating a user profile, giving AI-based recommendations, and offering support and guidance. This makes it a full solution that not only helps choose a career but also encourages and comforts users during the decision process. Because it’s scalable and doesn’t cost much, this system can be used widely in schools, especially in areas where professional career advice is not easily available. The paper explains the system’s structure, discusses related work and research, and shares the expected results and future improvements.
KEYWORDS
Publication Date
10/9/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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