Python Programming for Data Science and GitHub Version Control

Entering the world of data science requires more than just knowing how to write code; you also need to manage your projects and collaborate professionally. This text-based course bridges the gap by teaching you both Python programming and version control fundamentals in one unified path. You will transition from a complete beginner to a confident practitioner capable of writing clean Python code, analyzing datasets, and tracking your work using Git and GitHub. You will learn to organize your code, collaborate with others, and build a portfolio of your data science projects. What you'll learn: 1. Understand foundational Python syntax, variables, data types, and control flow. 2. Apply essential data analysis techniques using modern libraries like pandas to manipulate datasets. 3. Configure Git and GitHub to track changes, manage project versions, and prevent data loss. 4. Write clean, readable Python code using modern practices like type hints and structured virtual environments. 5. Collaborate on data projects by creating repositories, committing changes, and managing branches. 6. Practice cleaning and preparing raw data for analysis through structured written exercises. The course begins with foundational programming and version control concepts, gradually moving into data manipulation and collaborative workflows. You will progress through clear written explanations, practical code examples, and conceptual exercises designed to reinforce your learning. This course is designed entirely for beginners with no prior programming or data science experience. Anyone looking to build a strong foundation in Python and version control will find this course accessible and practical. Start reading today to build your data science toolkit and learn how to manage your code like a professional.