📊 Python Data Science Mastery
From Data Manipulation to Advanced Visualization
📚 Prerequisites
This course assumes you have basic Python knowledge. If you're new to Python, we recommend completing our Introduction to Python course first.
Quick Navigation
1 NumPy Fundamentals
Master the foundation of numerical computing in Python. Learn how NumPy arrays power the entire data science ecosystem.
2 Pandas Data Manipulation
Become a data wrangling expert with Pandas. Learn to load, clean, transform, and analyze real-world datasets with ease.
- 2.1 DataFrames & Series - Your Data Containers
- 2.2 Data Loading - Import from Anywhere
- 2.3 Data Cleaning - Handle Missing & Messy Data
- 2.4 GroupBy Operations - Split-Apply-Combine Magic
- 2.5 Merging & Joining - Combine Datasets Like SQL
- 2.6 Pivot Tables - Reshape & Summarize Data
- 2.7 Time Series Analysis - Work with Temporal Data
- 2.8 Window Functions - Rolling & Expanding Operations
3 Data Visualization Fundamentals
Transform numbers into insights with powerful visualizations. Master Matplotlib to create publication-quality figures.
4 Statistical Analysis
Apply statistical methods to extract meaningful insights from data. From descriptive stats to hypothesis testing.
5 SQL and Database Integration
Connect Python to databases and leverage SQL for powerful data operations. Work with both SQL and NoSQL databases.
6 Web Scraping & APIs
Gather data from the web efficiently and ethically. Master both static scraping and dynamic content extraction.
7 Advanced Visualization Libraries
Go beyond Matplotlib with modern visualization libraries. Create interactive dashboards and stunning statistical plots.