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.
- Variables, data types, loops, and conditionals
- File handling and error handling
- Object-Oriented Programming (OOP)
- Libraries: NumPy, Pandas, Matplotlib, Seaborn
- Data cleaning and manipulation
- Data visualization
- Handling missing values
- Outliers treatment
- Encoding (Label, Ordinal, Target)
- SMOTE for imbalanced datasets
- Summary statistics
- Correlation matrix
- Visualizations to identify patterns and trends
- Joins, Group By, Subqueries, Window Functions
- CTEs, Set Operations, and Aggregate Functions
- Power Query Editor for data shaping
- Building dashboards and visual reports
- DAX for advanced calculations