Choose the Right Tool for Your Data: Python, R, or SQL
I recently completed the LinkedIn Learning course taught by Megan Lieu on Python, R, and SQL for Data Projects, and it provided me with a solid foundation in understanding when and how to use each of these essential tools. The course clearly explained the strengths and limitations of each language, with real-world examples and case studies that helped me understand their practical applications in data analysis and beyond.
Through this course, I strengthened my ability to choose the right tool for different tasks—whether it’s Python for automation and machine learning, R for statistical analysis and visualization, or SQL for querying and managing databases. These insights are directly applicable to my career in data and analytics, as they help me work more efficiently, communicate technical choices more clearly, and build better end-to-end data solutions.