| School of Computer Science and Engineering |
Data Science and Big Data Technology |
1. General knowledge: be equipped with knowledge of humanities and social sciences, information and communication, law and environment, society and public security.
2. Basic knowledge of mathematics and natural science: master basic knowledge of higher mathematics, linear algebra, probability theory and mathematical statistics, etc. required for work related to the program.
3. Specialized basic knowledge: have a solid basic knowledge of computer programming, information processing methods, database technology knowledge, computer networks, object-oriented programming and other basic knowledge.
4. Specialized core knowledge: be familiar with the basic theories and methods in the professional field of data science and big data technology, master the basic thinking methods and research methods of big data science and technology, and be proficient in specialized knowledge including data analysis and methods, big data framework technology, data collection technology and data analysis.
5. Specialized elective and extended knowledge: choose different directions such as visualization technology, data mining technology, distributed database principles and applications, parallel and distributed computing principles, big data programming and development technology for professional expansion; master the knowledge of related courses in computer disciplines, expand students' comprehensive applications, big data literature retrieval, industry information searching and the use of modern information technology to obtain relevant knowledge; understand the application prospect of artificial intelligence related to big data technology, as well as the latest progress and development of related industries, and be able to combine the advanced knowledge of big data development with the study of courses in disciplines that have cross influence on other computer disciplines, and be able to expand the professional development independently. |
The minimum number of credits to be completed is 165, including 39 credits of required public courses, 10 credits of public electives (at least 2 credits in each category), 26 credits of specialized foundation courses, 27 credits of specialized core courses, 23 credits of specialized electives, 30 credits of concentrated laboratory courses, and at least 10 credits of extended courses |
