Previously taught courses.
Explores methods for representing, relating, and integrating information across text, images, audio, and other media. The course examines how complementary information sources support retrieval, recognition, and intelligent applications, helping graduate students understand research questions and methodological approaches in cross-media information processing.
Introduces the core concepts and major areas of computer science, including the relationships among computation, data, algorithms, programs, and computer systems. By connecting these ideas with representative problems and applications, the course builds an overview of the discipline and explains the role of computational thinking in problem solving.
Introduces the principles, layered architectures, and major communication protocols of computer networks. Through data transmission, addressing, routing, and end-to-end communication, the course connects protocol mechanisms with network behavior and familiar network applications.
Examines the organization, storage, and manipulation of data through common data structures and their associated algorithms. The course introduces abstract data types, algorithm efficiency, and implementation choices, emphasizing the selection of suitable structures and the design of programs that address both correctness and efficiency.