Data Science and big data Technology major cultivates application data engineer of comprehensive development in moral,intellengence,sports,aesthetics and labour education, which have good humanistic accomplishment,professional ethics,sense of social responsibility and team spirit,and master the theories and methods of computer,mathematics,statistics and so on, and master the techniques and means of big data’s gathering,processing,analysis and application,and have the ability of big data analysis and system development, and have strong engineering practice ability,autonomous learning ability, and innovative ability.
Students can enage in big data application development and system maintenance in information technology enterprises after graduation, and engage in big data analysis and mining,intelligent decision support and so on.
Six core courses are offered in the major, which includes 《data structure》, 《database principle and NoSQL database》, 《machine learning and python application》, 《data warehouse and data mining》, 《multivariate statistical analysis and R language modeling》, 《big data programming》.
1. Data Structure
《Data structure》is the basis of programming that deals with non-numerical computation.The purpose of this course is to train students to choose appropriate logic and storage structure for specific problem objects, to design appropriate algorithms for effective data storage and processing, and to cultivate students' ability to solve practical problems. This course can lay the foundation for subsequent courses.
2. Database Principle and NoSQL Database
《Database Principle and NoSQL Database》mainly teaches the basic concepts, basic principles and implementation techniques of relational and non-relational database.Students should master relational and non-relational data models, data theory, data operation language,database security protection, database design and so on by learning this course, so as to lay the foundation for students to engage in related work such as data management and system development. It is also ready for the future study of data warehouse, data mining, big data analysis and processing and other courses.
3. Machine Learning and Python Application
《Machine Learning and Python Application》focus on explaining the core algorithms and theories in machine learning, and cultivate students' basic ability of using machine learning algorithms to solve problems combing Python language. Through the study of this course, students have basic knowledge and preliminary skills of Python programming, understand common algorithms and typical application fields of machine learning, and train students' ability to analyze and solve practical problems through programming exercises and examples explanation, it can lay a good foundation for further study and research in the future.
4. Data Warehouse and Data Mining
《Data Warehouse and Data Mining》mainly introduces the data structure，data access method and application ,data preprocessing,data mining algorithm of data warehouse. Through the study of this course, students can understand the basic concepts, principles and methods of data warehouse and data mining, cultivate students' basic ability of analyzing data and acquiring knowledge, and lay a solid foundation for their future data analysis and data engineering practice.
5. Multivariate Statistical Analysis and R Language Modeling
《Multivariate Statistical Analysis and R Language Modeling》combines R language to explain the basic theories, methods and skills of multivariate statistical analysis. Students can master statistical analysis ideas and methods,use multivariate statistical methods to analysis and process data combining R language so as to solve some statistical analysis problems, and it lays a solid professional foundation for future analysis and research in the data field.
6. Big Data Programming
《Big Data Programming》focuses on the platform,development environment and basic principles of big data system, which makes students familiar with the mainstream big data application framework and its ecosystem, including Hadoop, Hbase, Hive, Spark, Spark SQL, Oozie and so on. Students should master the characteristics of mainstream big data system tools and platforms, the basic development methods of big data processing, the basic processes and methods of big data system construction, so as to cultivate students' program development ability based on big data tools and platforms. it will lay a foundation of big data system development and follow-up courses.