학술논문

Synergizing Futures: Precision Career Mapping with Llama 2 and AI Fine-Tuning for Personalized Path Prediction and Guided Navigation
Document Type
Conference
Source
2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) Communication, Computer Sciences and Engineering (IC3SE), 2024 International Conference on. :336-341 May, 2024
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Employee welfare
Engineering profession
Navigation
Scalability
Large language models
Design tools
Sparks
Student career guidance
Artificial Intelligence
Llama-2
Fine-Tuning
P3GS
Language
Abstract
These days, a lot of students struggle in how to choose the career. As they progress through their studies, students must recognize their abilities and assess their areas of interest to determine the most appropriate job for them. With the aid of this approach, today's youngsters will be able to determine which career route will yield the best outcomes in the long run if they choose the suggested vocation. This will assist in raising the student's performance and spark their interest to keep them concentrated on their desired job. This system is based on an exam that students must complete; based on their responses, it will produce a summary of the test results. The primary goal of this system is to give a summary of the artificial intelligence methods that we employed to forecast the student's performance. This structure likewise be emphasizing how we are identifying characteristics in student data by employing prediction systems. For educators, educational institutions, and students alike, using this system has proven to be advantageous. In this paper we have used various technologies like Flutter, Llama-2 generative A.I. model, Firebase and UI/UX design tools. Our experimental results of proposed system reduce the career searching effort by 80% when tested for Lyman people.