🎯 Internship Selection Analysis

A data analysis project focused on understanding internship selection trends, candidate performance, and hiring criteria using Python and exploratory data analysis.

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Project Overview

This project analyzes candidate data to identify factors affecting internship selection decisions.

Key objectives:

• Analyze candidate performance
• Compare selected vs rejected candidates
• Study CGPA and skill trends
• Explore project and GitHub score impact
• Visualize recruitment insights

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Tech Stack

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Jupyter Notebook

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Project Structure

Internship-Selection-Analysis/
│
├── data/
│ ├── internship_candidates.csv
│ └── cleaned_dataset.csv
│
├── notebook/
│ └── internship_analysis.ipynb
│
└── README.md

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Analysis Workflow

flowchart LR
    A[Candidate Dataset] --> B[Data Cleaning]
    B --> C[Performance Analysis]
    C --> D[Selection Comparison]
    D --> E[Visualization]
    E --> F[Insights]

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Key Analysis Performed

• Selection rate analysis
• CGPA comparison
• Skill distribution analysis
• GitHub/project score analysis
• Candidate performance trends

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Output

Prepared insights useful for:

• Recruitment analytics
• Candidate evaluation
• Internship trend analysis
• Hiring dashboards

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Future Improvements

• Machine learning prediction model
• Candidate recommendation system
• Interactive dashboard creation

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Report

This project is created only for educational and analytical purposes.
Plagiarism is strictly prohibited.

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