The students in major of Data Science should have the qualities of dedication, innovation, unity and cooperation, and have ideology and morality and professional ethics. They also should have scientific literacy, professional knowledge of the major and strong ability to adapt to the new environment. Good language (especially English) skills are necessary.
The graduates in major of Big Data engineering should be familiar with the four aspects of Big Data, namely data acquisition , management, analysis and applicaiton. They should have professional knowledge of BigData, master the technologies of computer, network, database, programming,data mining, and other related technologies of Data Science, and have practical ability and strong innovative capacity. They can engage in the research and development (R&D), system integration, maintenance and some other related work of BigData application fields such as intelligent transportation, environmental protection, geological disaster monitoring, government, public safety, safe home, smart fire protection, industrial monitoring, personal health, and etc.
After four years of comprehensive learning, the students should reach the following graduation requirements when they graduate.
Engineering knowledge: Being able to use mathematics, natural science, engineering fundamental and professional knowledge to solve complex engineering problems.
Analysis of issues: Applying basic principle of mathematics, natural science and engineering science to identify, express and analyze the DataScience and complex engineering problems through literature research, so as to obtain effective conclusions.
Design/development solutions: Designing solutions for the complex engineering problems of Data Science and BigData technology that not only meet the specific needs of the system, unit (components) or models ,but reflect the sense of innovation and consider the factors about social, health, safety, laws, cultural and environment in the design process.
Research: Using scientific methods to analyze the complex engineering problem of BigData based on scientific theories. The methods include design of experiment, analysis and interpretation of data and acquisition of rational conclusions through comprehensive information processing.
Applying modern tools: Being able to develop, select and use appropriate technologies, resources, modern engineering tools and information technology tools for the complex engineering problems of Data Science, which include predicting and simulating engineering problems, as well as understanding its constraints.
Engineering and society: Through correlative engineering background knowledge, rationally analyzing and evaluating the solutions on professional engineering practice and complex engineering of BigData, and not only its influence to society, health, safety, legal and cultural, but also its responsibilities.
Environment and sustainable development: According to the complex engineering problem of BigData, being able to understand and evaluate the impacts of professional engineering practices on the sustainability of environment and society.
Professional norms: Equipping with humanistic community scientific literacy and social responsibility, understanding and complying with the engineering professional morals and norms in engineering practices.
Individuals and teams: Playing the role of individual, team members and the person in charge in the team with multi-subject background.
Communication: Effectively communicating with the industry and the public about the complex engineering problem of BigData, which including reports writing and presentation, drafts designing and expressing or instructions responding, and having a certain international vision and the capability of communication and exchange in cross-cultural environments.
Project management: Understanding and mastering the theory of engineering management and economic decision method, and being able to apply them in multi-subject environment.
Lifelong learning: Having the awareness of autonomous learning and lifelong learning and the capability of continual learning and adapting to the development.