Learn Python programming, data structures, and core statistical concepts like probability, distributions, and sampling techniques.

Work with Pandas, clean datasets, handle missing values, detect outliers, and prepare data for analysis.

Create visualizations using Matplotlib and Seaborn, and present insights through effective data storytelling techniques.

Use SQL queries, joins, aggregations, and advanced functions to extract and analyze structured data efficiently.

Build regression and classification models, evaluate performance, and apply preprocessing techniques for better predictions.

Apply ensemble methods, clustering, dimensionality reduction, and feature engineering for improved model performance.