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Course Criteria
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4.00 Credits
Abstract models of computational systems. Classical models for uniprocessor, sequential, and stored program computers. New models based on recent advances in hardware, software, and communications and their implications in practice. (Lec. 3, Project 3) Pre: 340. In alternate years.
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3.00 Credits
See Mathematics 447.
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3.00 Credits
Concepts and techniques in discrete mathematics. Finite and infinite sets, graphs, techniques of counting, Boolean algebra and applied logic, recursion equations. (Lec. 3) Pre: junior standing or better in physical or mathematical sciences, or in engineering, or permission of instructor.
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4.00 Credits
Theories, formalisms, techniques to emulate intelligent behavior using information processing models. Symbolic programming, search, problem solving, knowledge-based techniques, logic, theorem proving. Optional topics: natural language processing, machine learning, computer vision. (Lec. 3, Project 3) Pre: 301 or permission of instructor. In alternate years.
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4.00 Credits
The science, technology, procedures, and law of acquiring and analyzing digital evidence from computers and devices (Lec. 3, Lab. 3/Online). Pre: 412, or permission of instructor.
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4.00 Credits
The science, technology, procedures, and law of acquiring and analyzing digital evidence from computer network activity (Lec. 3, Lab. 3). Pre: 485.
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1.00 - 4.00 Credits
Advanced work in computer science. Conducted as supervised individual projects. (Independent Study) Pre: permission of chairperson. S/U credit.
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1.00 - 4.00 Credits
Advanced topics of current interest in computer science. (Lec. 1 C4, Project 1 -3) Pre: permission of instructor.
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4.00 Credits
Supervised work on a capstone project in computer science that prepares students for careers in industry and graduate study. (Practicum) Pre: advanced standing in computer science and departmental approval. Normally taken twice in two consecutive semesters. May be repeated for a maximum of 8 credits. Not for graduate credit. S/U credit.
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4.00 Credits
Design, analysis, implementation, and comparative study of major programming language families. Topics include procedural and block-structured languages, interpretive languages, concurrency, functional languages, object-oriented programming, logic programming, dataflow languages and machines. (Lec. 3, Project 3) Pre: 301.
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