Usually we would think that the IT industry is stressful, the logic code is complex, and you need to think logically and be resistant to pressure in order to be a suitable programmer.

But in fact the whole IT industry to do big and strong at the very beginning is also from the foundation, like doing big data analysis. In yet to contact, for middle school students is very difficult, but follow the teacher's footsteps after a period of time, and will have a different feeling.

What students need to be able to do is to be patient with the technology and pay attention to the details, especially with the data, which requires accuracy.

From the perspective of the big data market in recent years, there are still more positions in the field of big data, especially big data development positions, which are gradually covering the field of big data application development from the development of big data platforms, which is the inevitable result of the beginning of the full application of big data.

The need for talent in big data development positions is more, and not only the need for R & D talent, but also the need for application-oriented talent.

Data science and big data technology majors in statistics, mathematics, computers for the three major supportive disciplines; biology, medicine, environmental science, economics, sociology, management for the application of expanding disciplines.

In addition to learning data collection, analysis, processing software, learning mathematical modeling software and computer programming languages, etc., the knowledge structure is a two-specialty multi-purpose composite cross-border talents (professional knowledge, and data thinking).

Different colleges and universities offer this program, the training mode will be different. Some will be more inclined to the use of tools, such as data cleansing, data storage, and data visualization and other related tools; some will be inclined to big data-related basic knowledge comprehensive coverage of the teaching , in the maturity of the stage will be to specialize in a technical field, such as data mining, data analytics, business intelligence, artificial intelligence, etc..

The main courses are: Mathematical Analysis, Advanced Algebra, General Physics, Introduction to Mathematics and Information Science, Data Structures, Database Principles and Applications, Computer Operating Systems, Computer Networks, Java Language Programming, Python Language Programming, Big Data Algorithms, Artificial Intelligence, Applied Statistics (Statistics), Big Data Machine Learning, Data Modeling, Big Data Platforms Core Technology, Big Data Analysis and Processing, Big Data Management, Big Data Practice and other courses.

Graduates of the Data Science and Big Data Technology program can engage in big data management, research, application development and other aspects of work in government agencies (prefecture-level cities have set up a special bureau of big data), enterprises, companies and so on. At the same time, they can get a graduate degree in software engineering, computer science and technology, applied statistics and other specialties or go abroad for further study.

More and more companies are focusing on data, from the Ministry of Defense to Internet startups and financial institutions, all of which need to be driven by innovation through big data projects.

There are also many positions that require data analysis or processing, such as food manufacturing, retail e-commerce, medical manufacturing, and transportation testing, to optimize inventory, reduce costs, and forecast demand.

Big data analytics talent is divided into three main categories: big data system development, big data application development, and big data analysis.

To learn more, pay attention to the "UW Vocational Education" public number.