Data science has its roots in statistics, computer science, and data analysis in the 1960s. It has since evolved into a multidisciplinary field that leverages advanced algorithms, machine learning, and artificial intelligence to uncover valuable insights and knowledge from data. Today, data science is more important than ever, enabling organizations to make data-driven decisions. The potential of data science is limitless, and its impact on the world is just beginning to be realized.
In this Series, we’ll delve into the fundamentals of data science, exploring the tools, techniques, and languages used to extract insights from data. From Python and R to SQL and PySpark, we’ll cover the most popular programming languages used in data science today. We’ll also explore niche, cutting-edge options, such as Julia, Scala, and Haskell, that offer unique advantages for specific use cases. Whether we’re new to the discipline or looking to expand our skillset, this Series will provide a solid foundation for building your knowledge and mastering the art of data science.
Throughout a collection of carefully-curated material, we’ll delve into the foundational knowledge of probability theory, statistics, optimization, computer science, software development, big data processing, and much more.