Computer Technology

Machine Learning

This course explores various learning algorithms and their applications, cultivating graduate students’ abilities to build models, learn models, and evaluate models from complex data. At the same time, through the data processing and modeling analysis of medium-scale practical problems, it trains graduate students’ abilities to analyze and implement artificial intelligence systems.

Algorithm Design and Analysis

This course cultivates postgraduates to correctly analyze the computational complexity of algorithms and to select and design algorithms. Through problem abstraction, algorithm design, and system construction of programming implementation, it solves an increasing number of complex practical application problems. This course enhances the postgraduates’ computational thinking ability, algorithm design ability, program design ability, and application ability.

Software Architecture

This course, through the introduction of concepts, design, and practical applications of software architecture, cultivates students’ awareness of software architecture design. It helps students understand the importance of software architecture in the development of complex systems and enhances their ability to analyze and design systems from a global perspective.

 Parallel Processing and Architecture

This course focuses on the design philosophy of high-performance computers and the mutual support between software and hardware. It discusses the common principles reflected in the structure and design of high-performance computers. The course cultivates postgraduates’ basic concepts and abilities in parallel computing models, architecture selection, and parallel program design. It also helps students understand the logical structure of high-performance computer systems and their subsystems.

Advanced Computer Networks 

This course, based on the undergraduate computer network course, further explores some high-tech and cutting-edge technologies in the field of computer network research and application, as well as modeling methods and simulation tools. It reflects the systematic, cutting-edge, and practical aspects of computer networks.

Computer Technology Practice

This course, with cutting-edge computer technology as the core theory, goes through various stages such as project planning, technical solution design, project implementation, testing, and deployment. It cultivates students’ ability to apply practical computer technology, enhances their problem-solving and innovation abilities, and enables students to independently complete computer-related projects.

Big Data Technology and Engineering

Machine Learning

This course explores various learning algorithms and their applications, cultivating graduate students’ abilities to build models, learn models, and evaluate models from complex data. At the same time, through the data processing and modeling analysis of medium-scale practical problems, it trains graduate students’ abilities to analyze and implement artificial intelligence systems.

Algorithm Design and Analysis

This course cultivates postgraduates to correctly analyze the computational complexity of algorithms and to select and design algorithms. Through problem abstraction, algorithm design, and system construction of programming implementation, it solves an increasing number of complex practical application problems. This course enhances the postgraduates’ computational thinking ability, algorithm design ability, program design ability, and application ability.

Software Architecture

This course, through the introduction of concepts, design, and practical applications of software architecture, cultivates students’ awareness of software architecture design. It helps students understand the importance of software architecture in the development of complex systems and enhances their ability to analyze and design systems from a global perspective.

 Parallel Processing and Architecture

This course focuses on the design philosophy of high-performance computers and the mutual support between software and hardware. It discusses the common principles reflected in the structure and design of high-performance computers. The course cultivates postgraduates’ basic concepts and abilities in parallel computing models, architecture selection, and parallel program design. It also helps students understand the logical structure of high-performance computer systems and their subsystems.

Big Data Technology and Application

Through the study of this course, students can systematically master the basic knowledge, principles, and methods of big data. They will initially have the ability to apply and develop big data, laying the foundation for engaging in big data analysis, modeling, and visualization.

Big Data Technology and Engineering Practice

Through actual projects and case studies, this course provides an in-depth understanding of the application and engineering practice of big data technology. It cultivates students’ mastery of the basic principles and application methods of big data technology and enhances their engineering practice ability. This course also improves students’ comprehensive literacy in the field of big data and their ability to solve practical problems.