Python Project 1 – Bank Loan Risk & Approval Analysis

📌 Topics Covered

• Loan applicant data analysis using Python
• Data cleaning and preprocessing
• Risk factors such as income, loan amount, credit history, and approval status
• Exploratory Data Analysis using pandas
• Basic visualization of approval and rejection patterns

📝 Project Summary

In this project, students will analyze bank loan application data using Python. The main goal is to understand which factors affect loan approval and which applicants may carry higher risk. Students will clean the dataset, explore applicant information, compare approved and rejected loans, and identify useful patterns that can support better loan decision-making.

✅ What You Will Learn

• Clean and organize loan application data using Python
• Analyze customer profiles and loan approval patterns
• Identify important risk factors behind loan rejection or approval
• Use pandas for grouping, filtering, and summary analysis
• Create basic visual insights from financial data

Note to Students –

Live Classes will held on Google Meet.
Mentor will provide files, dataset in the Google Classroom.
Class video will be provided on Google Classroom.

Click “Mark as Complete” button.

Good Luck.