All Courses(A-Z)
Course Code
CS 483
Course Name
Applied Parallel Programming
Credit
4.0 - 4.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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Introduction
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.
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Course Code
ECE 408
Course Name
Applied Parallel Programming
Credit
4.0 - 4.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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2021/2022 Fall Winter
Chan Kuan Yoow
2020/2021 Fall Winter
蔡童姜
2018/2019 Spring Summer
Lumetta, Steven
Introduction
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.
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Course Code
STAT4001
Course Name
Applied Statistics
Credit
2.0 - 2.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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2020/2021 Fall Winter
骆威
Introduction
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.
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Course Code
CS 440
Course Name
Artificial Intelligence
Credit
3.0 - 4.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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Introduction
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.
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Course Code
ECE 448
Course Name
Artificial Intelligence
Credit
3.0 - 3.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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2022/2023 Spring Summer
王宏伟
2020/2021 Fall Winter
王宏伟
2019/2020 Fall Winter
王宏伟
Introduction
<p>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.</p>
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Course Code
BT2341020
Course Name
Artistic Aesthetics
Credit
2.0 - 2.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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Introduction
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.
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Course Code
SOCW 297
Course Name
Asian Families in America
Credit
3.0 - 3.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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Introduction
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:
Blackboard
Course Code
F7123038
Course Name
Asset Pricing and Risk Management
Credit
2.0 - 2.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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Introduction
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.
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Course Code
BT2343044
Course Name
Audiovisual Language and New Media Communication
Credit
2.0 - 2.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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Introduction
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.
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Course Code
MATH 213
Course Name
Basic Discrete Mathematics
Credit
3.0 - 3.0
Instructors
Parent ID Semester (field_semester) - Any -2016/2017 Fall Winter2016/2017 Spring Summer2017/2018 Fall Winter2017/2018 Spring Summer2018/2019 Fall Winter2018/2019 Spring Summer2019/2020 Fall Winter2019/2020 Spring Summer2020/2021 Fall Winter2020/2021 Spring Summer2021/2022 Fall Winter2021/2022 Spring Summer2022/2023 Fall Winter2022/2023 Spring Summer2023/2024 Fall Winter2023/2024 Spring Summer2024/2025 Fall Winter2024/2025 Spring Summer
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2021/2022 Fall Winter
Thomas,Honold
2020/2021 Fall Winter
Schewe, Klaus-Dieter
2019/2020 Fall Winter
Schewe, Klaus-Dieter
2018/2019 Fall Winter
刘炜
2017/2018 Fall Winter
Thomas, Honold
Introduction
Beginning course on discrete mathematics, including sets and relations, functions, basic counting techniques, recurrence relations, graphs and trees, and matrix algebra; emphasis throughout is on algorithms and their efficacy. Credit is not given for both MATH 213 and CS 173. Prerequisite: MATH 220 or MATH 221, or equivalent.
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