Navigating Data Science: Theory and Practice

This chapter explores the journey of studying data science, emphasizing the differences between traditional university education and online courses. The discussion covers essential themes such as theoretical foundations in machine learning, the iterative process of building predictive models, and the critical role of domain knowledge in enhancing model performance. It highlights a structured approach to problem-solving, starting from basic models and progressively incorporating complexity to achieve better insights.