Data Science Fundamentals
Data Science Fundamentals refers to the basic building blocks and concepts that form the foundation of the field of data science. It includes topics such as statistics, probability, linear algebra, calculus, programming, data visualization, data cleaning, and database management.
Data Science Fundamentals refers to the basic building blocks and concepts that form the foundation of the field of data science. It includes topics such as statistics, probability, linear algebra, calculus, programming, data visualization, data cleaning, and database management. In addition, it covers the principles of machine learning and artificial intelligence, as well as the ethics and societal implications of data and AI. The goal of understanding the fundamentals of data science is to provide a strong foundation for further study and application in the field, allowing individuals to effectively collect, analyze, and interpret data to extract meaningful insights and drive decision making.