Career & Educational Advisor - Specialized For Engineering

The Career and Educational Advisor – Specialized for Engineering is an intelligent web- based recommendation and guidance system developed to assist students in exploring suitable engineering domains and academic opportunities. The project integrates machine learning concepts such as text vectorization and cosine similarity to analyze course descriptions and tags, enabling the system to recommend courses similar to the one selected by the user. This content-based approach focuses on measuring textual similarity rather than predictive model training, ensuring efficiency and interpretability. The application also includes interactive modules such as a career guidance quiz, government college search, and cutoff prediction to enhance user engagement and decision-making. It is implemented using HTML, CSS, JavaScript, and Python, along with libraries such as Flask, scikit-learn, Plotly, NumPy, and Pandas, and executed within Jupyter Notebook for data analysis and visualization. The system provides a unified platform for students to identify their interests, discover relevant courses, and align them with potential career paths in engineering. By combining data processing, natural language techniques, and interactive web design, the project aims to simplify the process of academic and career planning for aspiring engineers.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-12
DOI
https://doi.org/10.5281/zenodo.17586881
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Career & Educational Advisor - Specialized For Engineering

Zenodo (CERN European Organization for Nuclear Research)
Intelligent Tutoring Systems and Adaptive Learning
article

Career & Educational Advisor - Specialized For Engineering

article en

Abstract

The Career and Educational Advisor – Specialized for Engineering is an intelligent web- based recommendation and guidance system developed to assist students in exploring suitable engineering domains and academic opportunities. The project integrates machine learning concepts such as text vectorization and cosine similarity to analyze course descriptions and tags, enabling the system to recommend courses similar to the one selected by the user. This content-based approach focuses on measuring textual similarity rather than predictive model training, ensuring efficiency and interpretability. The application also includes interactive modules such as a career guidance quiz, government college search, and cutoff prediction to enhance user engagement and decision-making. It is implemented using HTML, CSS, JavaScript, and Python, along with libraries such as Flask, scikit-learn, Plotly, NumPy, and Pandas, and executed within Jupyter Notebook for data analysis and visualization. The system provides a unified platform for students to identify their interests, discover relevant courses, and align them with potential career paths in engineering. By combining data processing, natural language techniques, and interactive web design, the project aims to simplify the process of academic and career planning for aspiring engineers.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 22%
Intelligent Tutoring Systems and Adaptive Learning
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Career & Educational Advisor - Specialized For Engineering · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS