All notable changes to the Python Data Science Course will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Comprehensive documentation structure
- Development dependencies file
- Contributing guidelines
- MIT License
- Renumbered notebook structure (01-09) for better organization
- Investment portfolio analysis in Python basics notebook
- Enhanced pandas preview with real-world data examples
- Mini-challenges throughout all notebooks for interactive learning
- Self-assessment checklists at the end of each notebook
- Comprehensive README with badges, installation instructions, and professional formatting
- Troubleshooting section with common issues and solutions
- Hardware requirements table for optimal performance
- Project structure visualization with emojis and descriptions
- Course enhancement summary documenting all improvements
- Notebook naming convention: From mixed numbering to consistent 01-09 format
04.5_pandas_preview.ipynb→05_pandas_preview.ipynb- All subsequent notebooks renumbered accordingly
- Enhanced capstone project with more comprehensive analysis requirements
- Improved code comments and explanations throughout all notebooks
- Updated README.md to reflect new structure and highlight course features
- Modernized setup.sh script with better error handling
- Python basics notebook now includes:
- Investment portfolio calculation examples
- Real-world data analysis scenarios
- Interactive coding exercises
- Pandas preview expanded with:
- Data cleaning examples
- Visualization integration
- Performance optimization tips
- All notebooks now feature:
- Learning objectives at the beginning
- Progress checkpoints throughout
- Summary and next steps at the end
- README_COMPREHENSIVE.md: Professional-grade documentation with:
- GitHub badges and shields
- Detailed installation instructions
- Hardware requirements table
- Troubleshooting guide
- Performance benchmarks
- Contributing guidelines
- Updated course description files to match new structure
- Enhanced markdown formatting throughout all documentation
- Consistent code style across all notebooks
- Improved error handling in example code
- Better data visualization examples
- Enhanced code documentation with inline comments
- Optimized notebook performance for better user experience
- Initial course structure with 8 notebooks
- Basic Python programming concepts
- Data science fundamentals
- NumPy and Pandas introduction
- Matplotlib visualization basics
- Capstone project framework
- Requirements.txt with essential packages
- Basic setup script
- 01_python_basics.ipynb: Variables, data types, basic operations
- 02_control_structures.ipynb: If statements, loops, conditions
- 03_lists_data_structures.ipynb: Lists, tuples, sets
- 04_dictionaries_advanced.ipynb: Dictionaries and advanced concepts
- 04.5_pandas_preview.ipynb: Early introduction to Pandas
- 05_functions_modules.ipynb: Function definition and modules
- 06_numpy_fundamentals.ipynb: Array operations and mathematics
- 07_matplotlib_basics.ipynb: Data visualization
- 08_capstone_project.ipynb: Comprehensive final project
| Version | Release Date | Major Changes |
|---|---|---|
| 2.0.0 | 2024-12-19 | Complete restructure, enhanced content, professional documentation |
| 1.0.0 | 2024-01-01 | Initial release with core curriculum |
- Interactive widgets for better engagement
- Additional datasets for practice
- Video tutorial links
- Advanced machine learning preview
- Cloud deployment examples
- Advanced data science topics
- Deep learning introduction
- API integration examples
- Database connectivity
- Production deployment guide
Thanks to all contributors who helped make this course better:
- Course maintainers and developers
- Community contributors
- Beta testers and feedback providers
For detailed information about any release, check the commit history and pull requests.