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This lecture introduces the fundamentals of data science, covering topics such as the background of the instructor, the importance of data analysis, the breadth of data science methods, and the practical aspects of applied data analysis. It emphasizes the need for a comprehensive understanding of machine learning, data visualization, and handling large datasets. The lecture also highlights the significance of exploring data, building models, and communicating results effectively. Students are encouraged to focus on breadth rather than depth, enabling them to conduct full-fledged machine learning and data science projects. The course aims to equip students with the necessary skills to navigate the dynamic field of data science.