一、培养目标

本专业培养具有良好人文素养、道德修养、具有社会责任感和扎实数学基础，掌握信息与计算科学专业领域必备的基础理论、基本知识和专业技能，具有较强的实践能力和创新精神，且能够在数学、计算科学、大数据、信息技术、教育、医疗、信息产业、经济金融等领域从事研究、教学、应用开发、管理等工作的高素质应用型人才。学生毕业5年左右达到以下目标:

1.具有良好的人文素养、职业道德、社会责任感，关注当代全球和社会问题，有意愿并有能力服务于社会；

2.具备扎实的数学、计算科学、数据科学基础知识，掌握信息与计算科学专业相关领域的基础理论和专业知识，具有创新意识，以及处理专业相关复杂问题、设计与开发相关应用软件等方面的能力；

3.具备收集和构建信息，以最大的计算效率处理数据及分析数据能力；

4.应用统计、机器学习技术、软件工具等数据科学的技术、工具和方法应用于不同的应用领域，探索、管理、处理、利用和可视化数据；

5.具有文献检索和资料查询的能力，了解信息与计算科学前沿动态和发展趋势；

6.具有良好的表达和沟通能力以及团队合作和组织管理能力；

7.具有终身学习的意识,能够通过继续教育或其他学习渠道更新知识，实现综合能力和技术的提升；

8.具有国际视野和良好的外语应用能力。

I. Training objectives

This major trains undergraduate students to be high-quality applied talents with good literacy in humanities, professional ethics, social responsibility, and a solid foundation in mathematics. Students will master the necessary basic theory, fundamental knowledge, and professional skills in the field of information and computing science, with strong practical abilities and innovative spirit. Graduates will be able to engage in research, teaching, application development, management, and other work in various fields, including mathematics, computing science, massive data，information technology, education, medical treatment, information industry, economics, and finance, as highly skilled and applied talents. It is expected that graduates will achieve the following goals within five years after graduation:

1. Having good literacy in humanities, professional dedication, social responsibility, focusing on contemporary global and social problems, and having the willingness and ability to serve society;

2. Having a solid foundation in mathematics, computing science and data science, mastering the basic theory and professional knowledge in the field of information science and computing science, possessing the sense of innovation, and having the ability to deal with complex problems in computing science, and design and develop related application software;

3. Having the ability to conduct literature retrieval and data queries, understanding the latest trends and development in the field of information and computing science;

4. Having the ability of good expression and communication, as well as teamwork and organization and management;

5. Having the awareness of lifelong learning, being able to update knowledge and enhance comprehensive abilities and technical skills through continuing education or other learning channels;

6. Having an international perspective and good foreign language proficiency.

二、毕业要求

1.思想道德及职业规范：具有良好的思想道德素质和身体心理素质；具有良好的社会公德，自觉遵守社会行为规范；具有较强的法律意识，在法律法规规定的范畴内，按确定的相关标准和程序要求开展工作；具有良好的职业道德规范，自觉遵守职业行为准则。

2.数学基础及素养：熟练掌握高等代数-数据科学中的数学基础I、数学分析-数据科学中的数学基础II+III、概率论、数理统计等核心数学课程的理论和方法，并能在此基础上对复杂工程实际问题进行分析、推理、证明和计算。

3．数据分析与算法设计：能基于获取的数据对实际问题进行建模分析，并能设计算法对模型进行估计、诊断、比较和验证等；同时，要分析算法的稳定性、收敛性，估算其运算的时间、空间、复杂度等。

4.软件应用与开发：能运用信息与计算科学理论、方法和技能，将生产、生活中的实际问题提炼成数学问题，建立数学或者统计模型，给出解决方案，并能熟练使用C++、Matlab、SAS、R、Python等软件解决问题，并具备初步的软件开发能力。

5.数据收集及信息处理：能够基于数学原理对数据处理、性能评估及修正改进等复杂问题进行研究，包括设计实验、分析与解释数据、可视化等，并通过信息综合得到合理有效的结论。

6.社会责任意识：具有较强的社会责任感，能够基于信息与计算科学背景知识进行合理分析，利用设计、实施及评估规范评价信息与计算科学专业实践和复杂问题解决方案在环境保护、节约资源、公共安全、社会服务、社会福利、公共卫生、社会秩序等方面体现对社会的责任，如设计、实施及评估某些环境问题的解决方案等。

7.可持续发展：能够利用信息与计算科学的理论方法理解和评价复杂实际问题的实践对环境、社会可持续发展的影响。

8.综合素养：具有适应国家建设所需要的综合素质，包括文化素养、文学艺术修养、以及对历史学、哲学、思想道德、艺术、法学、社会学、心理学等方面的知识积累和理解。

9.团队合作：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，并具备一定的协调、管理、竞争与合作的能力。

10.书面沟通与语言沟通：能够就信息与计算系统设计、研究、开发等的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，能够在跨文化背景下进行沟通和交流。

11.国际视野：面向数学、信息、计算、数据科学等多学科环境，具有较强的外语应用能力，能够阅读本专业外文资料。

12.终身学习：具有较强的获取知识、终身学习的能力，能够紧跟信息科学与计算科学领域最新技术发展趋势，了解和学习本领域的最新技术知识和技术成果，不断提升自己的专业水平；具备收集、分析、判断、归纳和选择国内外相关技术信息的能力，不断补充自己的专业知识。

II. Requirements

1. Ideology and professional norms: have good moral and physical and mental qualities; have good social ethics and consciously abide by social norms; have a strong legal awareness and carry out work according to the relevant standards and procedures determined within the scope of laws and regulations; have good professional ethics and consciously abide by the occupation behavior criterion.

2. Mathematical foundation and literacy: proficiently master the classic principles, theories, methods, and applications of core mathematical courses such as advanced algebra-Mathematical Methods for Data Science I, mathematical analysis-Mathematical Methods for Data Science II+III, probability theory, mathematical statistics, and use this knowledge to analyze, reason, prove, and calculate complex practical engineering problems using scientific methods.

3. Data analysis and algorithm design: Capable of modeling and analyzing practical problems based on acquired data, and designing algorithms to estimate, diagnose, compare, and validate models; able to analyze the stability and convergence of the algorithm, and can estimate the time, space and operational complexity of the algorithm.

4. Software application and development: Capable to use the professional theories, methods and skills of information and computing science to refine practical problems in production and life into mathematical problems, establish mathematical models and give solutions, skilled in using C++, MATLAB, SAS, R, Python and other software to solve these problems, and have preliminary software development abilities.

5. Data collecting and Information processing: Able to conduct research on complex problems such as data processing, performance evaluation, correction and improvement based on mathematical principles, including designing experiments, analyzing and interpreting data, and drawing reasonable and effective conclusions through information synthesis.

6. Social responsibility awareness: Have strong sense of social responsibility, able to conduct rational analyses based on information and computing science background knowledge, evaluate the social responsibility of information and computing science professional practices and solutions to complex problems in environmental protection, resource conservation, public safety, social services, social welfare, public health and social order through design, implement and evaluate specifications.

7. Environment and sustainable development: Able to understand and evaluate the impact of practices on complex practical problems in information and computing science on environmental and social sustainability.

8. Comprehensive literacy: Have all kinds of cultural qualities which are suitable for national construction, including cultural accomplishment, literature and art accomplishment, knowledge of history, philosophy, ideology and morality, art, law, sociology, psychology and so on.

9. Teamwork: Ability to work as an individual, a team member, and a leader in a multidisciplinary team，have a certain ability of cooperation, management and competition.

10. Written and verbal communication: Ability to effectively communicate and communicate with industry peers and the public on complex engineering issues in the design, research and development of information and computing systems, including writing reports and design documents, making presentations, clearly expressing or responding to instructions, and communicating and communicating in a cross-cultural context.

11. International vision: In Math, information, computing and data science multidisciplinary environment, have strong foreign language application ability, able to read the foreign language materials of the major.

12. Lifelong learning: Have strong ability to acquire knowledge and lifelong learning, to keep up with the development of information and Computing Science in the field of new technology trends, understand and learn the latest technology in the field of knowledge and technology, and constantly improve their professional level; have the ability of collection, analysis, judgment, induction to select relevant technical information.

三、专业主干课程

统计学-数据描述与探索；C语言程序设计-编程I，II；数学分析-数据科学的数学方法II，III；高等代数与解析几何-数据科学的数学方法 I；概率论-风险和概率；数理统计-参数推理；统计计算与软件-统计软件I；回归分析-监督学习I；数据库系统概论-数据库；时间序列分析-时间序列；基于R语言的专业实验设计-统计软件II；基于Python的专业实验设计-数据科学和分析编程；多元统计分析-无监督学习；数据挖掘-监督学习II，III；数理金融-风险管理与评估；常微分方程；离散数学；C++程序设计；复变函数；数值分析；模式识别。

III. Core Courses and Characteristic Courses

Statistics-Data Description and Exploration; C programming-Programming I, II;

Mathematical Analysis-Mathematical Methods for Data Science II, III; Advanced Algebra and Analytic Geometry-Mathematical Methods for Data Science I; Probability Theory-Chance and Probability; Mathematical Statistics-Parametric Inference; Statistical Computing and Software-Statistical Software I; Regression Analysis-Supervised Learning I ; Introduction to Database Systems-Databases; Time Series Analysis-Temporal Series; Specialized Experiments and Design Based on R-Statistical Software II; Specialized Experiments and Design Based on Python-Programming for Data Science and Analysis; Multivariate Statistical Analysis-Non-Supervised Learning; Data Mining-Supervised Learning II, III; Mathematical Finance-Risk Management and Assessment; Ordinary Differential Equation; Discrete Mathematics; C++ Programming; Complex Function Theory; Numerical Analysis; Pattern Recognition.

四、基本学制：

学制为全日制4年。全部教学、科研活动均在中国武汉科技大学完成。

IV. Recommended length of the program:

The program duration is four year full time. All the teaching and research activities under the program will be conducted at WUST's campus in China.