The CAREER-INSIGHTS project aims to bridge the gap between the education system and the job market by predicting future career trends, admissions, and job opportunities in the fields of engineering, technology, pharmacy, and management. The platform utilizes machine learning models to analyze demographic data and provide insights into career prospects, admissions, and placement trends.
The project highlights a significant disconnect between the courses offered at the undergraduate and postgraduate levels and the evolving needs of the job market. This system employs Multiple Linear Regression, KNN, Random Forest, and XGBoost to form an integrated framework for predicting future job sectors, admission trends, and placements. Additionally, the project involves the creation of custom datasets for state-wise admission & placement in India, district-level data for Gujarat, startup trends, and institutional analysis, aggregated from multiple sources.
In India, unemployment remains a major concern, and students often lack awareness of future career opportunities while selecting their graduation courses. The changing industry demands require an adaptable system that keeps pace with evolving job trends. CAREER-INSIGHTS helps students make informed career choices by analyzing:
- Job trends in various industries
- Future predictions of course demand
- Placement trends in different domains
- Industry demands vs. academic curriculum
- Program trends after SSC
- Trending skills analysis for curriculum upgradation and learning
By integrating AI-driven analysis with real-world data, this project seeks to align education with employment opportunities, ensuring students acquire relevant skills for the future job market.
| Technology | Description |
|---|---|
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Extreme Gradient Boosting for optimized ML models |
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Ensemble learning for accurate predictions |
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K-Nearest Neighbors for classification |
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Predicting numerical trends |
| Technology | Description |
|---|---|
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Backend JavaScript runtime |
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Frontend UI framework |
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NoSQL database for scalable storage |
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Lightweight web framework for Python |
To get started, ensure you have Git, NPM, Node.js, and Python installed.
1️⃣ Clone the repository and install dependencies:
git clone https://github.com/your-repo/career-insights.git
cd career-insights
npm install2️⃣ Start the Client:
cd client
npm install
npm start3️⃣ Start the Server:
cd server
npm install
npm start4️⃣ Start the Flask Server:
cd flask-server
pip install -r requirements.txt
python app.py- Predicts trending job sectors based on demographic and industry trends.
- Provides insights into the demand for specific courses in engineering, management, and pharmacy.
- Analyzes historical admission data to predict future enrollments.
- Tracks placement records for different institutions and courses.
- Identifies gaps between industry needs and current course content.
- Helps universities update curriculum based on job market trends.
- State-wise and district-wise analysis of admissions and placements.
- Analyzes student preferences after SSC to determine popular programs.
- Helps in guiding students toward in-demand courses.
- Identifies trending skills needed in various industries.
- Recommends curriculum upgradation for better employability.
