Python Development: Data Science, Testing, and Distribution

Writing basic Python scripts is a great start, but taking your code to a professional level requires learning how to handle data, write automated tests, and distribute your work. This text-based course guides you step-by-step through the core practices of modern Python development, showing you how to structure data science projects, ensure code quality, and share your packages with others. You will learn to: * Understand foundational data science concepts by cleaning and analyzing datasets with modern libraries. * Implement automated testing using pytest to ensure your code remains reliable and bug-free. * Apply type hints and dataclasses to write self-documenting, clean, and maintainable Python code. * Configure modern packaging and distribution workflows to share your libraries with the community. * Create clear written data visualizations and reports using standard plotting libraries. You will start with the absolute basics of data structures and testing principles before moving on to hands-on written exercises that simulate real-world development workflows. This course is designed for learners who know basic Python syntax and want to learn how to structure, test, and distribute real-world data applications. No prior experience with testing or packaging is required. Start reading today to elevate your Python programming and build distribution-ready data projects.