I. Project Background
Data is a fundamental national strategic resource. The rapid development of social networking, cloud computing, Internet of Things, e-commerce and mobile Internet has brought human society into a new ? Big Data era? According to IDC statistics, the total amount of global data to double every two years of explosive growth, and at the same time gave birth to a large number of positions related to big data processing, through the mining and analysis of data to influence the government and enterprises and institutions to make decisions, in foreign countries is known as data scientists (Data Scientist). CareerCast, a U.S. career consulting website, announced that four of the ten jobs in 2017 were from data analysis-related fields, namely, statistician (Statistician), operations research analyst (Operation Research Analyst), data scientist (Data Scientist), mathematician ( Mathematician). Currently, Big Data analytics is very prevalent in North America, and has become one of the core competencies of various industries in society.
On September 5, 2015, the State Council issued the "Outline of Action for Promoting the Development of Big Data", which systematically deploys the development of big data. The Outline states that ? Encourage colleges and universities to set up majors related to data science and data engineering, focusing on cultivating big data professionals such as specialized data engineers. Encourage the adoption of cross-school joint training and other ways to carry out interdisciplinary big data comprehensive talent training, and vigorously cultivate cross-border composite talents with multidisciplinary knowledge of statistical analysis, computer technology, economic management, etc.? This means that China's big data development ushered in the top-level design, officially upgraded to a national strategy.
Therefore, how to respond to the real needs of social development, how to cultivate interdisciplinary big data composite talents with multidisciplinary knowledge has become a problem that needs to be solved in China's higher education. Big data science and engineering discipline direction is produced in the context of the big data era, the integration of information technology, statistics and management, economics and other disciplines, with the help of big data analysis for the community to solve problems in various industries as the main axis of the integration of related courses to form a new course system; is to train to be able to provide the government, enterprises and public institutions, groups of companies, financial services companies, etc., economic analysis, market research, The new specialty is to train high-end analytical, managerial and decision-making talents who can provide economic analysis, market research, intelligence research, data collection and integration and other information services for governmental enterprises and institutions, and financial service companies.
Objectives
Big Data Science and Engineering is based on the concept of "Internet+". Internet +? background of the real needs, cultivate mastery of economic management theory knowledge, with management practice skills, with data modeling and analysis capabilities, can have effective use of information technology advanced tools of composite talents, to solve the actual demand for talent, to promote? Internet+? The company's business is also a major player in the industry.
The courses offered by this subject direction are mainly divided into three parts: professional degree courses, disciplinary core courses and professional elective courses. Professional degree courses mainly include advanced statistics, computational statistics, principles of artificial intelligence, big data management and analysis, theory of computation, algorithm design and analysis and other aspects of the course, which is the foundation of graduate education in big data science and engineering disciplines; disciplinary core courses include management of fuzzy mathematical modeling, big data business analytics, data mining theory and algorithms, mathematical finance, machine learning, knowledge management and other courses
The core courses of the discipline include Management Fuzzy Mathematical Models, Data Mining Theory and Algorithms, Mathematical Finance, Machine Learning, Knowledge Management, etc., which focus on cultivating students' research ability on algorithms for big data analysis; in the part of the professional elective courses, students can independently choose relevant courses according to their own career development expectations; the courses include Big Data and Financial Analytics, Principles of Artificial Neural Networks, Deep Learning, Advanced Econometrics, and Frontiers of Big Data Science and Engineering.
III. Research Directions and Teams
The main research directions in the subject area of Big Data Science and Engineering are:
(1) Fundamental Theory of Big Data Computing
(2) Economics and Management in a Big Data Environment Research
(3) Business analysis and financial research based on big data
(4) Industrial management research in big data environment
(5) Bioinformatics research in a big data environment
(6) Theory and technology of big data management and analysis
The discipline direction of Big Data Science and Engineering is jointly established by the School of Management with the School of Computer Science and the School of Science, based on the strengths, origins, and specific features of the School of Management, combined with the computer knowledge of the School of Computer Science and the mathematical foundation of the School of Science, to build ? Management Science and Engineering + Computer Science and Engineering + Statistics? The model of the discipline makes the discipline more comprehensive for the training of graduate students, and students can choose different colleges to study according to their needs.
The subject clusters of the discipline of big data science and engineering mainly include, big data and ? Internet+? management and decision-making research in the environment, e-health research based on big data, business data analysis and artificial intelligence theory and methodology research, emerging financial technology and financial innovation research based on big data and artificial intelligence, big data-driven government governance and public **** service research, business innovation research in the big data environment, big data-based financial statistics theory and methodology innovation research, application-oriented big data management and analysis theory and technology research.
IV. Admissions
The interdisciplinary direction of Big Data Science and Engineering admits undergraduate graduates of computer science (especially computer science and technology majors), management science and engineering majors, as well as other related engineering majors and management majors. Relying on the disciplines and examination subjects as shown in the attached table, the enrollment plan is included in the overall plan of each faculty (department), and the specific number of enrollment is determined by each faculty (department) according to the registration and examination.
Table 1 Enrollment Catalog for the Master's Program in Big Data Science and Engineering
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