In recent years, data majors and artificial intelligence majors have been the most popular. There are 4 data majors: Data Science and Big Data Technology (Computer, 080910T), Big Data Management and Application (Management, 120108T), Applied Statistics (Big Data, Statistics 071202), and the newly established Data Science major in 2023 (Science, subject code 071203T). This article analyzes data science and big data technology under the computer category, the number of words in the article is too long, I will publish it in two parts. After writing the major of data science and big data technology, I will analyze the big data management and application major under the category of analysis and remanagement.
Today on the first day of the college entrance examination, it is fast to apply for volunteering, I am not an institution, I can write articles idly
First, is the major of data science and big data technology good?
A friend's child scored 486 points in the college entrance examination in 2022 (39 points lower than the special batch line) and was admitted to the data science and big data technology major of a municipal university, and enrolled in the first year, crying to withdraw from school and repeat his studies. Is it necessary?
The data science and big data technology major began to enroll new undergraduates in 2016, from the first batch of 3, to 730 in 2022, and 30 new colleges and universities recorded by the Ministry of Education in 2023, with a total of 760 universities meeting the application needs of parent candidates. If you add the enrollment scale of big data-related majors of higher vocational colleges, by 2028, the graduates at all levels will reach about 70,000. Will there be a surplus? Don't worry, there's still a talent gap. According to the "China Internet Hottest Job Talent Report" released by LinkedIn (LinkedIn), the big data talent gap will reach 2.3 million in 2025, according to the forecast report released by the China Academy of Information and Communications Technology in 2015, the talent gap in 2020 is 1.5 million, the latest year's report I have no money to buy or see, it is estimated that it is also lacking, lacking, lacking, anyway, according to the scale of such a college, by 2030, the total number of big data graduates is only about 400,000, That's a lot less than the nearly 300,000 graduates in computer science and technology each year.
Mainland is in the process of digital transformation, generating a large amount of data. Data not only refers to the massive information released by people on the Internet, but also includes a variety of structured and unstructured data generated by various equipment, buildings, systems, personnel, businesses, scenarios, etc., which measure and transmit various states and changes of objects at any time, which is an era of big data. Data is an important factor of production, a strategic resource related to national security, and is written into formal national documents and laws. Big data technology is based on data as the research object, which solves the collection, mining, processing, analysis and application of complex data. Big data has been widely used in the Internet, finance, telecommunications, power grid, transportation, health care, government, agriculture, geographic information, new media and other fields. The year before last, a total of 16 provinces across the country established big data middle schools, and I don't know if there has been an increase in recent years.
Zhejiang cloud computing data center
The reason for the astonishing expansion of enrollment in data science and big data technology majors is amazing. On the one hand, the demand for data talents for social digital transformation has surged, and national policies have vigorously supported it. In 2016, the country's first big data comprehensive pilot zone was officially settled in Guizhou, so the filing of Guizhou big data major is also more supported by the Ministry of Education, of course, the computer strength of Guizhou University is also very strong. On the other hand, it also shows that the major of data science and big data technology is not difficult to open this major. Although the Teaching Steering Committee of Computer Science of the Ministry of Education has established a "big data" professional group, it has not formulated professional standards like mature majors such as computer science and technology or software engineering. The core curriculum of data science and big data technology is composed of three parts: mathematics, statistics, and computers.
Data science and big data technology can be regarded as the transformation and evolution of applied statistics, penetrating and intersecting new disciplines generated by computer and artificial intelligence technology. Therefore, as long as there is mathematics or statistics, computers are basically the standard configuration of all schools, and it is relatively simple to open a big data major. Therefore, in recent years, applied statistics has been cut in large quantities, not because there are too many professionals, but because a large part of applied statistics has been upgraded to big data. It doesn't matter if there is no transformation, apply to the Ministry of Education to establish a new major in statistics - data science.
May 27, 2023, China International Big Data Industry Expo
Second, is it difficult to learn data science and big data?
There are two types of degrees in data science and big data: engineering degrees and science degrees. Some schools are science, some schools are engineering degrees, and some schools (such as Xiamen University and Shanghai University of Finance and Economics) have both science and engineering, and are enrolled in different colleges. Statistically, the big data for engineering degrees is 3 times that of science.
In addition to the difference in degrees in this major, each school will often combine the industry-specific background or academic expertise of its own school to add special courses. For example, a science degree must strengthen mathematics or statistical theory in the curriculum, while an engineering degree strengthens big data processing in computers and artificial intelligence, or the application of big data in a special engineering category of an industry. Do these differences between data science and big data majors have an impact?
When choosing a school, pay attention to distinguishing between institutions. Because if you choose a science degree, you will generally have more courses in mathematical statistics, such as more emphasis on the basics of mathematics, the basic mathematics course of science majors generally chooses mathematical analysis and advanced algebra, and general engineering majors choose advanced mathematics and linear algebra. In addition to courses related to big data analysis, mathematics courses such as operations research and optimization and statistical courses such as multivariate statistical analysis are generally offered, emphasizing the ability of mathematical modeling. Both science and engineering emphasize the analysis methods under big data, such as machine learning and data mining. The engineering major emphasizes computer-related courses, such as computer networks, computer composition principles and other courses. Engineering majors pay more attention to big data development, such as Hadoop series courses, while science majors pay more attention to big data analysis, such as statistics-related courses.
If it is a big data major of an industry-specific college, it depends on the type of school.
For example, big data in medical colleges, a total of 18 medical schools across the country will open this major in 2022, and the big data majors of these colleges are mainly to cultivate outstanding data engineers in the field of health and medical big data. For example, Shanghai Health Medical College sets up courses such as health big data visualization and health data mining according to the health theme of the college. Big data of Guizhou Medical University is the direction of medical big data, and Inner Mongolia Medical University has set up an introduction to Mongolian medicine in the big data professional course, and so on.
If it is a finance and economics school, it is the direction of financial big data. For example, graduates of the University of International Business and Economics majoring in big data are able to engage in data analysis in the fields of economics, finance, management, logistics, and commerce; The professional characteristics of Shanxi University of Finance and Economics are condensed as "finance + big data"; Jilin University of Finance and Economics majors in big data, adding more than 10 special courses such as Western economics, accounting, financial engineering, economic data analysis methods, business big data analysis, etc., and big data of Nanjing Audit University is big data + auditing.
If it is big data of agriculture-related schools, it is generally big data + smart agriculture, and the category of agricultural big data is complex, and it is not inferior to intelligent manufacturing data at all. Therefore, China Agricultural University's original big data has engaged in double degree enrollment, and now I don't know if there is any change.
If it is a strong logistics school, for example, Beijing Institute of Materials has "Beijing Intelligent Logistics System Collaborative Innovation Center" and "Beijing Key Laboratory of Intelligent Logistics System", which is a combination of big data + intelligent logistics. However, I have the impression that intelligent logistics is stronger than University of Science and Technology Beijing, right?
If it is a big data major of public security colleges, then the public security attribute is stronger. For example, the big data courses of the China Criminal Police College include the basics of public security data work, enterprise/public security big data systems and platforms, enterprise/public security big data analysis and visualization, and so on.
Big data visualization platform for an intelligent manufacturing enterprise
So what impact do these different differences have on the choice of institutions for everyone?
The article is too long, I will post it again in the next article. If you are interested, take a look again. If there is any mistake in the article, welcome to refute and point out, give parents and candidates the correct life guidance, thank you very much!