Bridging the Data Science Knowledge Gap

This chapter explores the motivations and challenges of writing a technical book focused on data science education, addressing gaps in existing literature and practical applications. It emphasizes the importance of foundational skills, the necessity of building robust portfolios, and understanding business objectives prior to data analysis. Additionally, the chapter critiques traditional methods, advocating for an adaptive approach that embraces real-world complexities and iterative questioning.