Week 1: Python Foundations for Data Work
- Introduction to Python environment (Jupyter, Anaconda, VS Code)
- Variables, data types, and operators
- Control structures: loops and conditionals
- Functions and modules
Hands-on: Write Python scripts for basic calculations
Week 2: Data Handling with Pandas & NumPy
- Introduction to NumPy arrays and operations
- Pandas Series & DataFrames
- Importing datasets (CSV, Excel, SQL)
- Data cleaning: handling missing values & duplicates
Hands-on: Clean a dataset using Pandas
Week 3: Data Analysis & Visualization
- Descriptive statistics in Python
- Grouping, filtering, and aggregating data
- Data visualization with Matplotlib & Seaborn
- Creating charts: line, bar, histogram, scatter, heatmaps
Hands-on: Build a visualization dashboard in Python
Week 4: Applied Data Analysis Project
- Exploratory Data Analysis (EDA) process
- Feature engineering basics
- Automating repetitive tasks with Python
- Case Study: Analyze a real-world dataset end-to-end
Mini Project: Present insights using Python visualizations
