Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

Parallel programming with emphasis on developing applications for processors with many computation cores. Computational thinking, forms of parallelism, programming models, mapping computations to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, and application case studies. 4 graduate hours. Prerequisite: ECE 220.

Parallel programming with emphasis on developing applications for processors with many computation cores. Computational thinking, forms of parallelism, programming models, mapping computations to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, and application case studies. Same as CS 483 and CSE 408. 4 undergraduate hours. 4 graduate hours. Prerequisite: ECE 220.

This course provides students with the elementary statistical tools and concepts needed in applications, beyond those learnt in the Mathematical Statistics course. Topics include: ANOVA, linear regression models and relative Statistical inferences, modern inferential methods, variable selection, dimension reduction, classification, etc. Following the theoretical materials are some real application examples for the students to comprehend the Statistical data analysis procedures. Emphasis is on understanding and tackling data analysis.

Major topics in and directions of research in artificial intelligence: basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225.

Major topics in and directions of research in artificial intelligence: basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225.

This course is a degree program for graduate student of Zhejiang University. It includes three parts: a) The history and the key concept of Contemporary Art Aesthetics, the main-stream of the area of modern arts theory and social critical theory. b) Some important theory correlative to the study of public arts and important theoretical progresses in Contemporary Art Aesthetics. c) Some important theorist of contemporary aesthetics, such as Foucault, Deleuze, Agamben, Ranciere.

Offers a comparative analysis of Asian families as they cope and adapt to American society. Examines: 1) how families from four major Asian-American groups (Chinese, Indian, Japanese and Korean) function in American society; 2) how these families compare to families in their country of origin; and 3) how these families are similar to or different from the 'typical American' family. Includes visits to Asian cultural institutions and with Asian families. Same as AAS 297 and HDFS 221. This course satisfies the General Education Criteria for:

This course will first teach theoretical aspects of both asset pricing and risk management, then the application of both asset pricing and risk management will be discussed in detail. Asset pricing and risk management will be both theoretically and empirically explored in detail. Real-world examples will be used to enhance students’ understanding of both asset pricing and risk management.

Audio visual language is the most basic part of the study of film and television creation - the basic law of lens combination, is a creative activity with a high degree of creativity, which includes two aspects: the level of creation and the level of skill. In the creation of film and television, editing thinking should run through the program creation.