数据科学与大数据技术专业毕业要求：
Graduation requirements
本专业的学生应具有爱岗敬业、求实创新、团结合作的品质；具有良好的思想品德、社会公德和职业道德。应具有良好的科学素养、较强的创新意识；具有全面的文化素质、良好的知识结构和较强的适应新环境、新群体的能力，以及良好的语言（中、英文）运用能力。
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.
数据科学与大数据技术专业毕业生应熟悉大数据产业链中数据采集、数据管理、数据分析和数据应用四个环节，掌握计算机、网络、数据库、程序设计、数据挖掘等数据科学与大数据技术专业知识和技能，能从事大数据技术研究方面的工作，又可以从事大数据技术应用、维护等工作，既具有较强的实践工作能力又具有创新能力的高层次大数据技术人才。学生毕业后能胜任大数据技术在智能交通、环境保护、地质灾害监测、政府工作、公共安全、智能家居、智能消防、工业监测、个人健康等领域的应用工作。
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.
经过四年的系统学习，本专业学生在毕业时应达成以下毕业要求：
After four years of comprehensive learning, the students should reach the following graduation requirements when they graduate.
1.工程知识：能够将数学、自然科学、工程基础和专业知识用于解决大数据复杂工程问题。
Engineering knowledge: Being able to use mathematics, natural science, engineering fundamental and professional knowledge to solve complex engineering problems.
2.问题分析：能够应用数学、自然科学和工程科学的基本原理，识别、表达、并通过文献研究分析数据科学复杂工程问题，以获得有效结论。
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.
3.设计/开发解决方案：能够设计针对大数据复杂工程问题的解决方案，设计满足特定需求的系统、组件或模型，并能够在设计环节中体现创新意识，考虑社会、健康、安全、法律、文化以及环境等因素。
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.
4.研究：能够基于科学原理并采用科学方法对大数据复杂工程问题进行研究，包括设计实验、分析与解释数据、并通过信息综合得到合理有效的结论。
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.
5.使用现代工具：具有利用现代信息技术获取相关信息的初步能力，具有综合运用所学理论和技术手段，分析并解决数据科学实际问题的基本能力；
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.
6.工程与社会：能够基于工程相关背景知识进行合理分析，评价专业工程实践和大数据复杂工程问题解决方案对社会、健康、安全、法律以及文化的影响，并理解应承担的责任。
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.
7.环境和可持续发展：能够理解和评价针对大数据复杂工程问题的专业工程实践对环境、社会可持续发展的影响。
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.
8.职业规范：具有人文社会科学素养、社会责任感，能够在工程实践中理解并遵守工程职业道德和规范，履行责任。
Professional norms: Equipping with humanistic community scientific literacy and social responsibility, understanding and complying with the engineering professional morals and norms in engineering practices.
9.个人和团队：能够在多学科背景下的团队中承担个体、团队成员以及负责人的角色。
Individuals and teams: Playing the role of individual, team members and the person in charge in the team with multi-subject background.
10.沟通：能够就大数据复杂工程问题与业界同行及社会公众进行有效沟通和交流，包括撰写报告和设计文稿、陈述发言、清晰表达或回应指令。并具备一定的国际视野，能够在跨文化背景下进行沟通和交流。
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.
11.项目管理：理解并掌握工程管理原理与经济决策方法，并能在多学科环境中应用。
Project management: Understanding and mastering the theory of engineering management and economic decision method, and being able to apply them in multi-subject environment.
12.终身学习：具有自主学习和终身学习的意识，有不断学习和适应发展的能力。
Lifelong learning: Having the awareness of autonomous learning and lifelong learning and the capability of continual learning and adapting to the development.
