Computer Science

This course focuses on data analysis and guides students to learn a series of data analysis methods. It covers the use of different data analysis tools for data analysis. It covers data acquisition, data cleaning, data selection, data manipulation, data calculation, data grouping and time series, etc. Based on the theoretical understanding, students will learn to use Excel and Python programming language to process data. 

This course focuses on data and programming structures for the development of macros and applications developed with Visual Basic for Applications (VBA) in the Microsoft Office suite. Other topics include: creating PivotTables for data analysis; creating functions, forms, and menus; an introduction to R language. Pre-requisites: Information Skills; IT Management.

The course is designed to prepare students for leadership in a globally interdependent and culturally diverse workforce. Throughout the course, students are challenged to question, think, and respond thoughtfully to the issues they observe and encounter in the internship setting, and the designated city in general. Students have the opportunity to cultivate the leadership skills as defined by the National Association of Colleges and Employers (NACE), such as critical thinking, teamwork, and diversity. Assignments focus on building a portfolio that highlights those competencies and their application to workplace skills. The hybrid nature of the course allows students to develop their skills in a self-paced environment with face-to-face meetings and check-ins to frame their intercultural internship experience. Students complete 45 hours of in-person and asynchronous online learning activities and 225-300 hours at their internship placement.

This course provides an introduction to operating systems, viewed from both the user and the programmer's point of view, and from the machine side. It also provides insight into how today's data communication is taking place and how to create programs that use such communication. The programming language C is used, and a basic introduction is given.

This course examines basic algorithms and models of artificial intelligence. Starting from the basic concepts of artificial intelligence, it systematically introduces various learning tasks to help students understand and master mainstream AI models and algorithm tools, gradually establish artificial intelligence thinking patterns, and improve their ability to analyze and solve practical problems.

This course covers the fundamental concepts of how computers perform at machine and assembly language level. It looks at the design of an instruction set architecture and figures out what makes a Reduced Instruction Set Computer (RISC) differ from a Complex Instruction Set Computer (CISC). The course discusses basic design principles by understanding the components in a computer and the performance of a computer system.  

This course provides the required background for students who are interested in designing computer systems, doing serious development of operating system kernels and device drivers, and making better applications of computer systems.   

Course prerequisites: A background in Digital Logic, C Language and Assembly Language is required.  

This course covers fundamental and advanced domains in human-computer interaction: interactive technologies, such as multi-touch, augmented/virtual reality, haptics, wearables, and fabrication.   

Course Prerequisites: It is recommended to take CSIE3311 Computer System Laboratory and CSIE5646 Interactive System Design and Implementation prior to this course. 

This course explores topics of machine learning and deep learning, examining both the foundations and applications of the topics. Starting with the basics of how to pre-process data, the course then ventures into linear models. Further topics include cross validation, support vector machines, kernels, regularization, boosting, bootstrap aggregating, and stacking.

This course introduces the basic principles and hardware structures of a modern programmable computer. Students will explore computer architecture as the science and art of selecting and interconnecting hardware components to create a computer that meets functional, performance and cost goals. 

 Students will learn how to design the control and datapath for a pipelined RISC processor and how to design fast memory and storage systems. The principles presented in lecture are reinforced in the laboratory through design and simulation of a register transfer (RT) implementation of a RISC processor pipeline in Verilog.