View count: 11347
With the development of science and technology and the changes in social needs, the boundaries between the old tradition and the contemporary society are more and more blurred; problems faced by contemporary society often need to be solved through new thinking, new methods and new tools. The “data science”, which collects, organizes, analyzes and interprets data, is a new cross-domain knowledge that has recently received much attention and has potential for future development. In short, data science is the transformation of data into knowledge that can be used for decision-making and action. As the availability of wide ranges of materials, it is significant and valuable to use this information and turn it into a decision-making basis for individuals, businesses and governments.
Data scientists need to be able to ask questions, gather relevant information, do the correct analysis, and translate the results so that it can be understood for decision making. Therefore, traditionally, data scientists need to have three capabilities: domain knowledge, mathematical analysis capabilities, and computer information capabilities. The different focuses on these three capabilities are the development of data science talents with different characteristics. The data scientists of the new era need to be able to explore and mine primary sources, in addition to organize and analyze the data accordingly. The design of the cross-domain expertise of the "Information Science and Social Analysis" is to hope to give full play to the traditional training and advantages of the College of Social Sciences in "domain knowledge" and "social analysis", and to further integrate the computer information capabilities required in the new era, educate students to have data analysis talents for the future scientific application of data.
In general, this cross-domain expertise is designed to develop cross-domain talent with knowledge, data, and quantitative analysis in the social sciences. The course design is based on the professional courses of each department of the school. It trains students' analysis and insight on contemporary economic, political and social issues. Combined with the core courses of the school and inter-departmental data science, the course is designed to build students' applications of computers and programs. Through the training of this course, students will have the ability to observe problems, collect data, analyze data, and interpret the results of analysis. As a result of the increasing number of digital data and calculus tools, they will be able to grasp opportunities and respond to the society.
-Host: Department of Economics, College of Social Sciences.
-Participants from the Teaching Unit: Department of Politics, Department of Economics, Department of Social Sciences, Graduate Institute of National Development, Graduate Institute of Journalism, Department of Computer Science and Information Engineering, Department of Information Management, College of Science, College of Electrical Engineering and Computer Science, College of Management, Center of General Education