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数据科学与大数据技术专业介绍

发布日期:2019-08-30    作者:统计信息管理员     点击:

数据科学与大数据技术专业

专业特色:2019年设立数据科学与大数据技术本科专业,同年开始招生。数据科学与大数据技术专业以统计学、数学和计算机科学为基础,以“新工科”教育理念为指导,立足东北老工业基地,瞄准国家大数据战略需求和国际数据科学学术前沿,与生命科学、医疗健康、经济金融等领域深度融合,形成了人工智能、互联网大数据、金融大数据和医疗大数据四个特色鲜明的研究方向。数据科学与大数据技术专业基于“产学研”相结合的人才培养模式,以国家大数据战略规划为指引,以社会需求为导向,立足本省,面向全国,放眼世界,致力于培养掌握数据科学的理论与方法,精通大数据处理与分析、算法研发、可视化等技术的高水平人才。

主要课程设置:数学分析、高等代数、空间解析几何、数据科学与大数据技术导论、概率论、数理统计、抽样技术与应用、数据结构、分布式存储与计算、实用统计软件、多元统计分析、数学模型、回归分析、Python数据分析、数据可视化、数据库、时间序列分析、最优化方法、大数据分析与实践

学生就业方向:毕业生能够在政府机构、工业、医药、互联网、教育、金融等领域成为大数据科学相关教学、科研、开发和应用的大数据工程师、数据分析师和数据科学家。

Data Science and Big Data Technology

Major Features:

The Data Science and Big Data Technology major was found in 2019. Based on statistics, mathematics and computer science, the data science and big data technology major is guided by the "new engineering" education concept. Based on domestic tactical requirement on big data and international data science research frontier, the Data Science and Big Data Technology major has formed four distinctive research directions of artificial intelligence, Internet big data, financial big data and medical big data, by integrating Data Science with Biology, Medication and Health Care and Finance. Based on the talent cultivation mode of combining "production, study and research", this major cultivates talents that master the theory and method of data science, and are proficient in big data processing and analysis, algorithm research and development, visualization and other technologies.

Curriculum:

Mathematical Analysis, Advanced Algebra, Space Analytic Geometry, Introduction to Data Science and Big Data Technology, Probability Theory, Mathematical Statistics, Sampling Technology and Application, Data Structure, Distributed Storage and Computing, Applied Statistical Software, Multivariate Statistical Analysis, Mathematical Model, Regression Analysis, Python Data Analysis, Data Visualization, Data Base, Time Series Analysis, Optimization Method, Big data analysis and Practce.

Graduation:

Graduates can become big data engineers, data analysts and data scientists that undertake the teaching, research, development and application tasks in the fields of government, industry, medicine, internet, education, finance and so on.

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