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Course Criteria
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0.00 - 4.00 Credits
This is a course about the practice of programming. Programming is more than just writing code. Programmers must also assess tradeoffs, choose among design alternatives, debug and test, improve performance, and maintain software written by themselves & others. At the same time, they must be concerned with compatibility, robustness, and reliability, while meeting specifications. Students will have the opportunity to develop these skills by working on their own code and in group projects.
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0.00 - 4.00 Credits
An introduction to mathematical topics relevant to computer science. Combinatorics and probability will be covered in the context of computer science applications. The course will present a computer science approach to thinking and modeling through topics such as dealing with uncertainty in data and handling large data sets. Students will be introduced to fundamental concepts such as NP-completeness and cryptography that arise from the world view of efficient computation.
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0.00 - 4.00 Credits
An introduction to computer architecture and organization. Instruction set design; basic processor implementation techniques; performance measurement; caches and virtual memory; pipelined processor design; design trade-offs among cost, performance, and complexity.
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0.00 - 4.00 Credits
Provides an opportunity for a student to concentrate on a "state-of-the-art" project in computer science. Topics may be selected from suggestions by faculty members or proposed by the student. The final choice must be approved by the faculty advisor.
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0.00 - 4.00 Credits
The fundamental principles, algorithms and techniques of modern artificial intelligence research and practice. Likely topics include: problem solving using search, game playing, logical inference, probabilistic reasoning in the presence of uncertainty, hidden Markov models, speech recognition, Markov decision processes, machine learning.Two 90-minute lectures.
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0.00 - 4.00 Credits
Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms. Introduction to NP-completeness.
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0.00 - 4.00 Credits
Introduction to computer graphics. Topics include image synthesis, 3D modeling, image processing and animation. Encourage hands-on experience.
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0.00 - 4.00 Credits
Security issues in computing, communications, and electronic commerce. Goals and vulnerabilities; legal and ethical issues; basic cryptology; private and authenticated communication; electronic commerce; software security; viruses and other malicious code; operating system protection; trusted systems design; network security; firewalls; policy, administration and procedures; auditing; physical security; disaster recovery; reliability.
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0.00 - 4.00 Credits
This course examines the methods used to search for information in large digital collections (e.g. Google) and how digital content is gathered by search engines. We study classic techniques of indexing documents and searching text and also new algorithms that exploit properties of the Web (e.g. links) and other digital collections, including multimedia collections. Techniques include those for relevance and ranking of documents, exploiting user history, and information clustering. We also examine systems aspects of search technology: how distributed computing and storage are used to make information delivery efficient.
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0.00 - 4.00 Credits
A hands-on introduction to the use of formal methods for reasoning about software, and for specifying and reasoning about programming languages. Students will use an interactive proof assistant to learn about logic and its applications to proofs of program correctness, to operational and axiomatic semantics of programming languages, and to type systems. Also, an introduction to functional programming languages.
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