Credit
Course Introduction
As an emerging discipline, data science relies on two factors: the breadth and diversity of data, and the commonality of data research. All walks of life in modern society are full of data. The types of data are diverse, including not only traditional structured data, but also unstructured data such as web pages, text, images, videos, and audio. Data science mainly includes two aspects: using data methods to study science and using scientific methods to study data. The former includes bioinformatics, astroinformatics, digital earth and other fields; the latter includes statistics, and its learning, data mining, database and other fields. These are all important parts of data science, but only by integrating them organically can the whole picture of data science be formed. The course includes the basic concepts and knowledge systems of data science, the basic processes and methods of data analysis (including intelligent analysis techniques such as data preprocessing, regression, clustering, and classification).
