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Course Criteria
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3.00 Credits
P: CSCI 36200 Techniques for analyzing and comparing algorithms are presented. Algorighms analyzed include those for sorting, searching, graph theory, comginatorics, computational geometry, matrices, and other problems. Computational complexity, including Turing Machines, NP completeness, and effecive computability.
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3.00 Credits
P: 36200. Overview of artificial intelligence; expert system technology; early expert systems: MYCIN, DENDRAL; theoretical foundations, uncertainty measures, knowledge representation, inference engines; reasoning mechanisms: forward and backward chaining; and explanation systems, expert system shells, tools, and intelligent hybrid systems.
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3.00 Credits
P: 36200. Study of key concepts and applications of artificial intelligence. Problem-solving methods, state space search, heuristic search, knowledge representation: predicate logic, resolution, natural deduction, nonmonotonic reasoning, semantic networks, conceptual dependency, frames, scripts, and statistical reasoning; advanced AI topics in game playing, planning, learning, and connectionist models.
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1.00 - 5.00 Credits
By arrangement. Fall, spring, summer. Supervised reading and reports in various fields. Open to students only with the consent of the department.
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1.00 - 6.00 Credits
Fall, spring, summer. Explorations in Applied Computing is an undergraduate capstone experience. Students will work in teams, advised by faculty and external liaisons, to solve real-world computing problems. This hands-on experience will cultivate technical expertise, utilization of analytical thinking, quantitative reasoning, project management skills, and communication skills.
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3.00 Credits
P or C: MATH 001, M001, or equivalent. No computing experience assumed. How computers work, word processing, spreadsheets, file management, and Internet skills. Emphasis on problem-solving tech-niques. Lecture and laboratory. Credit given for only one of CSCI N100, CPT 10600, CIT 10600, or BUS K201.
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1.00 - 3.00 Credits
Seminars in emerging technologies. May be repeated for credit.
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3.00 Credits
Summary of basic computing topics, problem solving techniques, and their application to computing. Introduction to programming concepts with a focus on language-independent principles, such as algorithm design, debugging strategies, essential control structures, and basic data structure concepts. Lecture and laboratory.
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3.00 Credits
Summary of basic computing topics. An introduction to data analysis using spreadsheets. Emphasis on the application of computational problem-solving techniques. Lecture and laboratory.
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3.00 Credits
Summary of basic computing topics. Introduction to database design concepts, creation of user forms, development of databases, querying techniques, and building reports. Focus on relational database systems from development and administration point of view. Lecture and laboratory.
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