| Days | Content Title | Key Concepts Covered |
| Days 1-7 | Tools & Data Handling | Python/Jupyter Notebook Setup, Introduction to NumPy (Array creation, indexing, operations), Introduction to Pandas (DataFrames, Series). |
| Days 8-14 | Data Cleaning & Preprocessing | Loading data, Handling missing values, Data filtering and selection, Grouping and Aggregation. |
| Days 15-21 | Data Visualization | Introduction to Matplotlib and Seaborn, Creating basic plots (Bar, Line, Scatter, Histograms), Telling stories with data. |
| Days 22-30 | Basic Statistics & Project | Descriptive Statistics, Introduction to Linear Regression (Conceptual), Final Project: Exploratory Data Analysis (EDA) on a public dataset (e.g., Titanic or Iris). |






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