SQL and GitHub Version Control for Data Science

To succeed in data science, you must know how to retrieve raw data efficiently and collaborate on code with other professionals. This text-based course bridges the gap between database querying and modern version control, giving you the exact technical skills industry teams expect. You will transition from manual data tracking to writing clean database queries and managing your analysis scripts like a professional developer. By reading through practical scenarios and code examples, you will learn to extract, clean, and organize data while keeping your work safely versioned and documented. What you'll learn: - Understand foundational database concepts, relational schemas, and essential SQL syntax. - Write queries to filter, aggregate, and join data from multiple tables. - Apply advanced SQL techniques, including Common Table Expressions (CTEs) and window functions, for complex analysis. - Master Git fundamentals to track changes, commit code, and manage project history. - Collaborate on GitHub by managing repositories, branch workflows, and pull requests. - Utilize modern AI tools to assist in writing, debugging, and optimizing your SQL queries safely. The course begins with core database terminology and basic SQL commands before moving into advanced data manipulation. You will then explore version control workflows, learning how to integrate Git and GitHub seamlessly into your daily data science pipeline. Designed for beginners, aspiring data scientists, and Excel users looking to upgrade their technical skills, this course requires no prior programming or database experience. Start reading today to build a solid foundation in data retrieval and collaborative version control.