What is the direction of data science and big data technology at Fudan?

According to the general direction of data science and data engineering of the School of Computer Science of Fudan University, it also belongs to the Shanghai Key Laboratory of Data Science. At present, this research group focuses on the research of data analysis and mining algorithms centered on web data, social networks, and social big data. In recent years, he has mainly participated in national projects, key projects, national 863 projects, Shanghai Science and Technology Commission Innovation Plan, foreign cooperation projects and other projects.

His research focuses on the design and implementation of data modeling, data mining, information dissemination, behavior and other algorithms in the big data environment. Specific research includes (but is not limited to):

**Research on community detection algorithms in social networks; **Research on information spreading in social networks and influence maximization;

2.Research on the analysis algorithm and financial market prediction algorithm of financial big data based on microblogging news and comments;

3. Establishment and application of knowledge graph based on big data analysis of social networks (e.g., using knowledge graph to influence learning);

4 Design and implementation of big data-based data mining algorithms (clustering, classification, deep learning) in parallel environment;

5. Data modeling and data query of scientific big data; (currently participating in the international cooperation SKA astronomical big data analysis);

The main tasks of graduate students in the laboratory are: participating in seminars, implementing algorithms and demo systems, participating in laboratory projects, and cooperating in high-level conferences or journals.

The laboratory provides: necessary experimental conditions, a certain work-study subsidy, and the ability to have direct and full discussion and guidance with you in a timely manner. (Some familiar foreign professors are able to make recommendations).

Basic Requirements:1. Good foundation in mathematics and strong active learning ability;

2。Interested in big data processing and analysis, with certain hands-on programming skills;

2020 College Entrance Examination Voluntary Filling, Big Data Professional Interpretation.

I'm from Tianjin University.

's undergraduate major, the current major is mathematics, which was a major enrollment at that time.

At present, there is no diversion of Burning Lee's majors, but in the future, the majors will be data science and big data technology.

Data science and big data technology are interdisciplinary disciplines.

Statistics, mathematics and computer science are the three basic disciplines, and biology, medicine, sociology, management and other disciplines are expanded. If you can learn well, you will become a compound talent. The outlook is still quite good.

After graduation, students can engage in data science research and intelligent analysis, processing, mining and application of big data in various industries.

However, you must realize that mathematics in college is very rare compared to other subjects, you must have a clear understanding and grasp of your own ability, and not to mention how good you learned mathematics in high school, you can learn well in college, this is a very wrong idea, because elementary mathematics and mathematics majors in middle school are really not comparable at all, and the learning methods are different. (I'm struggling to study now, but to be honest, if you're willing to work hard, don't hang too many subjects, you can still have a diploma.)

In addition, the School of Mathematics is also very busy and tiring).

And I would also like to remind you that most of the questions in math majors are proof questions. Our basic course includes mathematical analysis.

Advanced Algebra, Topology, Complex Variable Functions.

If you are interested, you can learn about real functions, abstract algebra, mathematical statistics, probability theory, etc.

Fundamentals of the discipline.

Good.

1. From the perspective of the current technological development trend, industry development trend and social development trend, the development prospects of the field of big data are very broad, and big data itself will also open up a huge value space, thereby creating a new industrial ecology, and this process will inevitably release a large number of jobs.

2. From the perspective of technology development trends, as many enterprises have realized business to the cloud, the next step will inevitably be based on the cloud computing platform to complete the integration and value of data, which needs to be achieved with the help of big data technology. From this point of view, in the future, not only the IT Internet industry needs big data talents, but also the industry also needs a large number of big data professionals, and the demand for talent types is also very diversified, whether it is a graduate student, an undergraduate student or a junior college student, they can find a suitable position for themselves.

3. From the perspective of industry development trends, we are currently in an important period of industrial structure upgrading, and the industrial Internet is becoming a new driving force for the development of traditional enterprises, which will prompt more enterprises to complete the innovation and development of enterprises based on the Internet. The era of industrial Internet is the era of platformization, and technology platforms such as cloud computing, big data, and artificial intelligence will gradually begin to be applied, so the development trend of the industry will also promote the development and application of big data.

4. From the perspective of social development trends, with the application of 5G communication, the whole society will gradually enter a digital and intelligent era in the future, at this time, the value of data will be further improved, and the value of data will mainly rely on big data technology to complete, so the development and application of big data technology is also an inevitable result of social development.

Finally, big data technology itself is a huge technical system, people with different knowledge structures can choose the entry point of learning big data based on their actual needs, so even people who are not computer majors can learn big data, and learning big data related technologies is also a big development trend.

The prospect of big data is very good, a major like big data is better in first-tier cities, teachers can keep up, and the salary of employment is also considerable, and learning big data can be <> in the order of the roadmap

Data science and big data employment directions include data analysts, data engineers, machine learning engineers, data mining engineers, etc.

Knowledge Expansion:

Data analysts are responsible for collecting, collating, and interpreting large amounts of data and turning it into valuable insights and decision support. They need to be familiar with statistics, data mining, data visualization and other technologies, and be able to use relevant tools and programming languages for data processing and analysis.

Data engineers are mainly responsible for building and maintaining big data platforms and related infrastructure to ensure the efficient acquisition, storage, and processing of data. They need to have solid knowledge of programming and database technology, be familiar with big data processing frameworks (such as Hadoop, Spark), etc., and be able to design and implement reliable data processes and architectures.

Machine learning engineers work to develop and apply machine learning algorithms and models to solve complex, data-driven problems. They need to have knowledge of mathematics, statistics, and machine learning theories, be familiar with commonly used machine learning algorithms and tools, and be able to perform data preprocessing, feature engineering, and model evaluation.

Data mining engineers focus on discovering and extracting useful information and patterns to support business decisions and analysis. They need to be familiar with data mining algorithms, statistical analysis methods, and related tools to be able to analyze and interpret complex data and turn it into actionable insights.

Data product managers are responsible for applying data science to product development and innovation. They need to have an interdisciplinary technical and business understanding and be able to work closely with data science teams to understand user needs and deliver practical data product solutions.

Through the above career pathway selection, you can decide your own employment direction according to your interests, skills and experience. In addition to the rapid development of data science and big data, there are many other employment directions, such as data governance experts, data privacy experts, artificial intelligence ethics experts, etc., which need to be selected according to personal development plans and industry needs.

Summary. With the popularization of mobile Internet and smart terminals, the convergence and integration of information technology and economy and society have triggered the rapid growth of data. At present, the top priority is to solve the bottleneck of big data talents, and relevant surveys show that the big data talent gap will reach as much as 1.5 million in the next 3-5 years.

There is still a high demand for data science and big data technology professionals, but as of now, there are only about 300,000 big data practitioners in China. With the extension and development of big data to various vertical fields, there is an increasing demand for talents majoring in statistics and mathematics, as well as software fields such as data analysis, data mining, and artificial intelligence.

With the popularization of mobile Internet and smart terminals, the convergence and integration of information technology and economy and society have triggered the rapid growth of data. At present, the top priority is to solve the bottleneck of big data talents, and relevant surveys show that the big data talent gap will reach as much as 1.5 million in the next 3-5 years. There is still a high demand for professionals in data and big data technology, but as of now, there are only about 300,000 data practitioners in China.

With the extension and development of big data to various vertical fields, there is an increasing demand for talents majoring in statistics and mathematics, as well as software fields such as data analysis, data mining, and artificial intelligence.

What are the future employment directions?

Graduates majoring in big data and accounting can be employed in cashiers, general ledger accounting, auditing, cost accounting, current settlement accounting, accounting computerization positions in large and medium-sized enterprises, audit assistants and tax planning positions in the bookkeeping post and accounting intermediary service industry, bank tellers, financial planners, financial managers, brokers, and financial departments of large and medium-sized enterprises.