Release Date: 2022-07-27

The Data Computation and Application major is an applied science program that integrates mathematics, statistics, and information science. It was established in response to the rapid development of the data industry. In 2022, this major received approval from the Hebei Provincial Department of Education and launched a "2+2 Double Degree Joint Training Program" with the University of New South Wales, Australia (ranked 38th in the 2021 QS Global University Subject Rankings and first in Australia). The program offers mutual recognition of credits between Chinese and foreign universities. Students participating in the program study at both institutions; the first two years at Hebei Normal University, and the third and fourth years at the foreign university. Students who meet the academic requirements are eligible to receive bachelor's degrees from both Chinese and foreign universities, as well as a bachelor's degree certificate from Hebei Normal University.

1. Training Objectives

Amidst the rapid development of the data industry, the program aims to cultivate politically steadfast, well-rounded individuals with solid mathematical foundations and mathematical thinking abilities. Students will master basic theories, methods, and skills in mathematics, statistics, and information science. They will receive preliminary training in scientific research, possessing capabilities in data modeling, high-performance computing, big data processing, and programming. The program focuses on applying knowledge and skills to solve practical problems in data analysis, information processing, scientific and engineering computing, and more. Students are expected to have strong self-learning abilities, innovative thinking, international perspectives, and effective communication skills.

2. Graduation Requirements

2.1 Ideological Beliefs: Firm political beliefs, practice of core socialist values, and identification with socialism with Chinese characteristics.

2.2 Professional Quality: Commitment to the data industry with a strong sense of social responsibility, understanding and adherence to professional ethics and norms.

2.3 Physical and Psychological Health: Strong physique, willpower, psychological quality, and a positive life attitude; dedication to data science.

2.4 Labor Ethics: Respect and love for labor, diligent work ethic.

2.5 Cultural and Scientific Literacy: High level of humanistic and scientific culture.

2.6 Knowledge Structure: Solid understanding of mathematics, statistics, and information science; good mathematical literacy; mastery of data science thinking and research methods.

2.7 Ability Structure: Necessary natural and humanities knowledge for data computation work, strong mathematical foundation, scientific thinking, basic theoretical knowledge in data science, and the ability to apply data mining theories and methods.

2.8 Research Training: Preliminary scientific research training, knowledge updating, and innovation skills; basic scientific research ability.

2.9 Self-learning: Skills in literature search and use, lifelong learning philosophy, ability to analyze self-development in line with the times and needs of information and computing science.

2.10 Teamwork and Communication: Ability to undertake roles in multidisciplinary teams, effective communication with peers and the public, including writing reports and speeches. Some international perspective, organizational management, and social competition and cooperation skills.

3. Main Courses

Mathematical Analysis, Advanced Algebra, Analytical Geometry, Introduction to Data Science, Mathematical Modeling, Probability and Mathematical Statistics, Statistical Machine Learning, Operations Research and Optimization, Data Mining, Mathematical Foundations of Artificial Intelligence, Econometrics, Discrete Mathematics, Complex Functions, Digital Image Processing, Algebraic Topology, Data Cleaning and Fusion.