Graduate classes, Fall 2018, Computer Science

CS 523: Data Structure & Algorithms ICredits: 3− Description− Sections
Content: This course introduces practical algorithms and data structures, for students entering graduate computer science from other fields of study.
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Prerequisites: The prerequisites are introductory programming and some discrete mathematics, which we expect our entering students already have. Students who have taken an undergraduate algorithms course (similar to our CS 323, and typically included in a Computer Science major) may place out.
1MSC: W301MW 4:00pm - 5:15pmMichelangelo Grignimax 30
CS 526: AlgorithmsCredits: 3− Description− Sections
Content: This course is a graduate level introduction to the design and analysis of algorithms. Although we will review some undergraduate level material, we will instead emphasize reading and experimentation at a level appropriate for the initiation of research. This course will have both theoretical and practical content. As course highlights, students will be expected to implement and analyze the performance of a fundamental data structure, starting with a close reading of the original research paper.
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Prerequisites: CS 224 and CS 253.
1MSC: W303MW 1:00pm - 2:15pmMichelangelo Grignimax 30
CS 534: Machine LearningCredits: 3− Description− Sections
Content: This course covers fundamental machine learning theory and techniques. The topics include basic theory, classification methods, model generalization, clustering, and dimension reduction. The material will be conveyed by a series of lectures, homeworks, and projects.
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Prerequisites: Cross-listed with BIOS 534. Knowledge of linear algebra, multivariate calculus, basic statistics and probability theory. Homework and project will require programming in Python, Matlab, C/C++ or R. Or permission by the instructor.
1MSC: W301TuTh 1:00pm - 2:15pmJoyce Homax 30
CS 551: Systems ProgrammingCredits: 3− Description− Sections
Content: Systems programming topics will be illustrated by use of the Unix operating system. Topics include: file i/o, the tty driver, window systems, processes, shared memory, message passing, semaphores, signals, interrupt handlers, network programming and remote procedure calls. Programming examples and assignments will illustrate the system interface on actual computer hardware. All assignments will be in written in C. The department's computing lab will be used in the course to allow students to get hands-on experience with operating system and hardware topics that cannot effectively be pursued on a central timesharing computer.
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1MSC: W301TuTh 2:30pm - 3:45pmKen Mandelbergmax 20
CS 554: Database SystemsCredits: 3− Description− Sections
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1MSC: W301TuTh 11:30am - 12:45pmShun Yan Cheungmax 30
CS 557: Artificial IntelligenceCredits: 3− Description− Sections
Content: This course covers core areas of Artificial Intelligence including perception, optimization, reasoning, learning, planning, decision--making, knowledge representation, vision and robotics.
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Prerequisites: Undergraduate level of Artificial Intelligence or Machine Learning.
1MSC: W303TuTh 10:00am - 11:15amEugene Agichteinmax 15
CS 573: Data Privacy and SecurityCredits: 3− Description− Sections
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1MSC: W303MW 10:00am - 11:15amLi Xiongmax 20
CS 584: Topics in Computer Science: Computer SecurityCredits: 3− Description− Sections
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3MSC: W301MW 2:30pm - 3:45pmYmir Vigfussonmax 10
CS 584: Topics in Computer Science: Programing LanguageCredits: 3− Description− Sections
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2MSC: W303MW 11:30am - 12:45pmJames Lumax 5
CS 590: Teaching SeminarCredits: 1− Description− Sections
Content: This course explores theoretical and practical approaches for effective teaching, with particular emphasis on the discipline of Computer Science. After this course, students will be able to demonstrate knowledge of multiple pedagogical strategies, write a syllabus, develop assessment items, and design and deliver lectures and presentations for a variety of different audiences.
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1MSC: W201F 2:00pm - 2:50pmSteven La Fleurmax 40
CS 597R: Directed Study: Professional DevelopmentCredits: 1− Description− Sections
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1MSC: W301F 2:00pm - 3:00pmShun Yan Cheungmax 30
CS 597R: Directed StudyCredits: 1 - 9− Description− Sections
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2Ymir Vigfussonmax 2
CS 599: CS ResearchCredits: 1 - 9− Description− Sections
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1Jinho Choimax 5
2Dorian Arnoldmax 5
3Gari Cliffordmax 5
4Lee Coopermax 5
5Li Xiongmax 5
6Joyce Homax 5
7Ymir Vigfussonmax 5
CS 700R: Graduate SeminarCredits: 1− Description− Sections
Content: This is a required course for all students in the PhD program. It comprises seminars given by faculty, invited guests, and students.
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1MSC: W201F 3:00pm - 4:00pmDorian Arnoldmax 30