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Course Criteria
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4.00 Credits
Introduction to programming and computational approaches to engineering problems and their solution. Matlab language illustrates principles such as data representation, mathematical operations, looping and decisions, functions and subroutines, display and user interaction. Projects from several different engineering domains have subjects like linear algebra, differential equations, fitting data to models, signal processing, and the practical use of analog-digital converters in an experimental setting.
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4.00 Credits
Organized thinking, creative problem solving, and the precise description of solutions are valuable skills in academia and life. The formulation and solution of problems using computers is increasingly important in all artistic and scholarly fields. We introduce core concepts and techniques of programming as a way to develop these skills, as basis for further CS study, and for application to other fields. Lab required.
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4.00 Credits
The course is taught using the Javascript programming language and HTML, but it emphasizes algorithmic thinking and creative problem solving over language specifics. Grades are based on projects and exams. Prospective majors lacking experience can take this course, possibly preceded even by CSC 108, in the freshman year, and begin the late-start B.A. in the fall of the sophomore year. This course also serves students who want to learn programming, but whose educational goals do not require the scope of coverage found in CSC 171. Lab required. Not open to officially declared CSC majors.
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4.00 Credits
Abstract data types (e.g., sets, mappings, and graphs) and their implementation as concrete data structures in Java. Analysis of the running times of programs operating on such data structures, and basic techniques for program design, analysis, and proof of correctness (e.g., induction and recursion). Lab required.
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4.00 Credits
This course explores the possibility of consciousness in machines, both in the sense of perceptual awareness and self-awareness. Readings are from the AI literature as well as from philosophy and cognitive science. The course will begin with some general philosophical and cognitive science readings, and then shift emphasis to representational and computational aspects. Homework will include written answers to questions, essays, and -- for 291 students only -- a project that involves Lisp programming. The course will be suitable for writing credit. (4 hours, Spring)
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4.00 Credits
Intensive seminar on cooperative problem solving. Overview of the subdisciplines and the research of the University of Rochester’s computer science faculty. 200H required for the Honors B.S. in Computer Science; 200 required for the B.S. Students taking CSC 200H may have additional reading, assignments or projects.
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4.00 Credits
Intensive seminar on cooperative problem solving. Overview of the subdisciplines and the research of the University of Rochester’s computer science faculty. 200H required for the Honors B.S. in Computer Science; 200 required for the B.S. Students taking CSC 200H may have additional reading, assignments or projects.
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4.00 Credits
An introduction to the technology, design and science of web programming. This course will cover the base material needed to create and deploy secure, usable database-driven web applications - including topics selected from programming, networking, databases, security, and usability. Specific technologies and languages covered will include HTML, Javascript, Document Object Model (DOM), PHP, MySQL, Ruby on Rails, XML, AJAX, and Flash.
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4.00 Credits
Introduces fundamental principles of artificial intelligence, including heuristic search, automated reasoning, handling uncertainty, and machine learning. Presents applications of AI techniques to real-world problems such as understanding the web, computer games, biomedical research, and assistive systems. This course is a prerequisite for advanced AI courses.
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4.00 Credits
. This course presents the mathematical foundations of AI, including probability, decision theory and machine learning.
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