An examination of the relationship between artificial intelligence (AI) and human intelligence. Topics include: the nature and limitations of the algorithmic method; how computers work; developments in computational learning and problem solving; and meaning of learning and/or thinking. Students address additional questions such as Can computers think?
; What is strong AI versus weak AI?
; and Can Computers be creative?
. This seminar develops written and oral communication skills with an emphasis on persuasive communication.
An examination of the pervasive nature of computer software and the impact that computer technology has on society. Drawing on articles from the popular press and the computer science literature, this course examines the technical and ethical challenges that face a culture that regularly uses computer software applications. Sample topics include the Internet, Google, iPods, online music, and electronic commerce. This seminar develops written and oral communication skills with an emphasis on persuasive communication.
| Instructor: | Yuting Zhang | | | course website |
| Location: | Alden Hall, Room 101 |
| Lecture: | M,W,F - 11:00 - 11:50AM | | | Lab Session: | Tues- 2:30 - 4:20PM |
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An introduction to the principles of computer science with an emphasis on algorithmic problem solving and the realization of al-gorithms using a modern object-oriented programming language. Topics include algorithms, problem solving, programming, classes, primitive data types and objects, control structures, arrays and vec-tors, principles of object-oriented design and programming, and an introduction to graphics and graphical user interfaces. The course also includes an overview of the discipline of computer science and a study of the social implications of computer use. May serve as the laboratory course in the Natural Science Division"s distribution requirement. One laboratory per week. Prerequisite: Knowledge of elementary algebra.
A continuation of Computer Science 111 with an emphasis on data structures, data abstraction, algorithm design, the analytical and experimental evaluation of algorithm performance, and object-oriented design and implementation techniques. Topics include stacks, queues, deques, lists, strings, trees and graphs, dictionaries, recursion, searching and sorting algorithms, and an introduction to program veri?cation. May serve as the laboratory course in the Natural Science Division"s distribution requirement. One laboratory per week. Prerequisite: Computer Science 111 or permission of the instructor.
Core Courses
| Instructor: | Yuting Zhang | | | course website |
| Location: | Alden Hall, Room 101 |
| Lecture: | M,W,F - 9:00 - 9:50AM | | | Lab Session: | TH - 2:30 - 4:20PM |
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A treatment of selected topics from the analysis of algorithms including models of computation, design of effcient algorithms, computational complexity, and NP-completeness. Students develop expertise in mathematical analysis and algorithmic programming methodology. One laboratory per week. Prerequisites: Computer Science 112 and Mathematics 205.
| Instructor: | Robert Roos | | | course website |
| Location: | Alden Hall, Room 101 |
| Lecture: | T,TH - 9:30 - 10:45AM | | | Lab Session: | M - 2:30 - 4:20PM |
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A survey of the theory, computational techniques, and applications of artificial intelligence. Topics include agents, knowledge representation, machine learning, general problem solving, natural language processing, neural networks, evolutionary computation, computer vision, robotics, and philosophical questions. One laboratory per week. Prerequisite: Computer Science 112. Offered in alternate years.
An examination of the principles and paradigms associated with the design, implementation, and analysis of distributed systems. Topics include the characterization of distributed system models, remote communication, distributed scheduling, synchronization and mutual exclusion, naming and time, consistency and replication, and fault tolerance. Selected distributed system development environments are discussed in the context of the above topics. One laboratory per week. Prerequisites: Computer Science 290 or 440 or permission of the instructor.
| Instructor: | Robert Roos | | | |
| Location: | Alden Hall, Room 103 |
| Lecture: | F - 1:30 - 2:30pm | | |
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A corequisite seminar for all students participating in the Intern-ship Program. Internship students enroll twice, once prior to and once following the Internship. Computer Science 550 focuses on expectations and planning, leading to the Internship Proposal required for all students planning an internship. Computer Science 551 provides the opportunity for students who have completed the Internship to prepare written and oral reports on the Internship experience. The student, in consultation with the faculty of the Department of Computer Science, is responsible for arranging for an acceptable internship. The courses meet together weekly for one-half a semester. Credit: One semester hour for each course. Prerequisites: Completion of at least two core courses.
CS 580. Junior Seminar: Topics & Research Methods in Comp. Sci. |
more info...
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| Instructor: |
Cupper
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Course website,
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| Location: | Alden Hall, Room 101 |
| Lecture: | T,TH - 11:00AM - 12:15PM | | | Lab Session: | F - 2:30 - 4:20PM |
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An advanced treatment of selected topics from various areas of computer science with an emphasis on appropriate research methods. Practical skills are acquired in technical writing, critical reading, and presentation of technical literature in preparation for the senior project. One laboratory per week. Prerequisite: Completion of the computer science core or permission of the instructor.
Continuation of independent research in computer science. Pre-requisite: Computer Science 600. Credit: Three semester hours
