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Academic Programs

Big Data Management and Application

 

The major of big data management and application focuses on serving the new quality productive forces, steps up efforts in promoting the high-quality development of the national and regional modern industrial system, and closely combines the data production elements with the demands of economic, social, and enterprise development. It highlights the new objectives put forward by the advancement of the nation and the development of enterprises to the professional big data management and application education under the new generation of information technological changes. Focusing on big data, artificial intelligence, blockchain, and other national strategies and industrial development directions, it cultivates versatile innovative talents who are rooted in local soil and culture but also have international competitiveness. It aims to meet the national strategic needs of accelerating the building of an education, sci-tech, and talent powerhouse.

This program mainly focuses on theoretical knowledge in the fields of management, economics, big data and artificial intelligence, and highlights the professional characteristics of integrating "teaching, learning, research, production, and application". All the students are equipped with professional scientific research supervisors and join the scientific research echelon. They will go to the relevant enterprises for research and professional internships, so as to strengthen the combination of theoretical knowledge learning and management practice and research. Graduates of this program are engaged in data analysis, algorithm development, product development, and other related technical work, or employed in related management positions in government departments, enterprises, and institutions, or continue to study for higher degrees in domestic and overseas educational and scientific research institutions.

Hunan University is one of the earliest educational institutions in China to offer a major in big data management and application, which began to enroll undergraduates in 2024. It now has become a nationally renowned program that includes three levels of undergraduate, master's, and doctoral training and education, with the right of granting scientific degrees.

Objectives

The big data management and application major aims to cultivate college students who master the basic theories of big data science and enterprise management; are familiar with the technology and methods of modern enterprise management; use the basic tools and methods of big data to carry out intelligent business analysis; and, implement enterprise management based on the big data platform and innovate the big data enterprise services and applications. The students are expected to become new academic talents in the future and senior management talents with international vision, innovation ability, and leadership potential, so as to meet the needs of enterprises and public institutions, governmental organizations, and scientific research institutes in the era of big data for management analysis, planning, decision-making and research. This program helps nurture students' following qualities:

1. Solid expertise and skills in big data management;

2. Effective communication skills;

3. An international perspective;

4. A sense of social responsibility; and,

5. Innovative spirit and entrepreneurial ability.

Educational System, Graduation Credit Requirements, and Degree Conferment (2024 Version)

1. The general duration of undergraduate study is 4 years, with a flexible study period of 3-6 years, managed according to the credit system.

2. The minimum graduation credits for students majoring in Big Data Management and Application is 150 credits, of which the required credits for courses and sessions of each category are listed in the table below:

Categories

Courses for General Education

Courses for Professional Education

Required credits for graduation

Compulsory Courses

(35-37 credits)

Obligatory Courses

(at least 10 credits)

Professional Compulsory Courses

Diversified Development Courses

Professional Basic Courses

(16-30 credits)

Professional Core Courses

(30-40 credits)

Other Practice Courses

(at least 4 credits)

Professional Obligatory Courses

(at least 8 credits)

Interdisciplinary Optional Courses

(at least 2 credits)

International Courses

(at least 2 credits)

Innovation and Entrepreneurship

(at least 4 credits)

Credits

37

10

29

35

11

18

4

2

4

150

3. Students shall be awarded the Bachelor's Degree in Management after completing all the credits according to the graduation requirements, attaining the standard test scores according to the National Standard for Students' Physical Fitness and Health, and having fulfilled the conditions for the degree conferment according to the Rules for Conferment of Bachelor's Degree on Full-time Undergraduates of Hunan University (No. 11 Teaching Document of the Hunan University〔2024〕).

Major Courses (2024 Version)

General Compulsory Courses: Ideology and Politics Series, College English, Situation and Policy, and Introduction to Computing and Artificial Intelligence.

Professional Basic Courses: Advanced Mathematics A, Linear Algebra A, Probability and Mathematical Statistics A, Principles of Economics, Management, Operations Research, Big Data Technologies and Applications, and Introduction to the Profession.

Professional Core Courses: Introduction to Philosophy, Advanced Programming, Introduction to Computing, Databases and Data Warehousing, Project Management, Introduction to Psychology, Machine Learning (S), Econometrics, Computer Networks and Applications, Data Governance Theory and Applications (S), Principles of Finance, Blockchain Technology and Applications, Systems Analysis and Design, and Data Asset Valuation and Trading.

Personality Development: Organizational Behavior, Financial Management, Operations Management, Game Theory, Data Compliance Management, Enterprise Legal Risk Management, Customer Relationship Management, Information Resource Management, Social Network Analytics, Multivariate Statistical Analysis and SPSS Applications, Cases of Industry Big Data Applications, Digital Finance and Fintech, and Advanced Machine Learning (S).