📊 My Data Analysis Learning Journey

Welcome to my personal learning journey in Data Analysis! 🚀
In this repository, I document everything I've learned — from the basics of Python to advanced concepts in SQL, Power BI, and machine learning pre-processing techniques.

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🔍 What's Inside?

🐍 Python Fundamentals

• Variables, data types, loops, and conditionals
• File handling and error handling
• Object-Oriented Programming (OOP)

📈 Data Analysis with Python

• Libraries: NumPy, Pandas, Matplotlib, Seaborn
• Data cleaning and manipulation
• Data visualization

🛠️ Feature Engineering

• Handling missing values
• Outliers treatment
• Encoding (Label, Ordinal, Target)
• SMOTE for imbalanced datasets

🔎 Exploratory Data Analysis (EDA)

• Summary statistics
• Correlation matrix
• Visualizations to identify patterns and trends

🧠 SQL for Data Analysis

• Joins, Group By, Subqueries, Window Functions
• CTEs, Set Operations, and Aggregate Functions

📊 Power BI & Data Visualization

• Power Query Editor for data shaping
• Building dashboards and visual reports
• DAX for advanced calculations

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🗂 Folder Structure