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Course Criteria
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3.00 Credits
Important features and concerns of implementation design on programming languages in common use today will be studied and analyzed. Includes data and control structures, run-time storage management, context-free grammars, language translation systems, programming paradigms, distributed and parallel programming constructs. Co/Prerequisites: CS 311, and MATH 270 or 370.
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3.00 Credits
Analyzes the social opportunities and problems raised by new information technologies. Emphasizes the dangers of incorrectly implemented software and hardware systems and relates them to the responsibilities of computing professionals. Effects of personal safety, quality of life, education, employment, personal privacy, organizational productivity, organizational structure, ethical values and regulations will be discussed. May not be taken for credit by students who have received credit for CS 303. Prerequisite: CS 311.
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3.00 Credits
Regular and context-free languages, and other formal languages, push down and finite-state automata, and other finite machines. Turning machine computability, halting problems. May not be taken for credit by students who have received credit for CS 521. Enrollment Requirement: MATH 270 or 370. Co/prerequisite: CS 351. Prerequisite: CS 311.
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3.00 Credits
Operating system design and implementation, process coordination and scheduling, deadlocks, interface devices, memory and device management, networks and security, distributed and real-time systems. May not be taken for credit by students who have received credit for CS 533. Enrollment Requirement: CS 231. Prerequisite: CS 311.
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3.00 Credits
Covers the fundamentals of networking concept and technology, which includes data communication, OSI 7-layer model, TCP/IP protocol stacks and the Internet, the features of LAN, MAN and WAN, network security, and basic CGI programming and web applications. May not be taken for credit by students who have received credit for CS 497D. Prerequisite: CS 311.
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3.00 Credits
Principles, techniques, and tools used to effect the orderly production of medium- and large-scale computer software will be studied. Includes review of problem-solving concepts, software development process, software requirements and specifications, verification, and validation. These techniques will be applied to programming projects with students working in teams and managing all phases of a programming project. Social, professional, and ethical issues will be discussed. May not be taken for credit by students who have received credit for CS 541. Enrollment Requirement: MATH 270 or 370. Prerequisite: CS 311
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3.00 Credits
Study of the concepts and structures necessary to design and implement database management systems. File organization, index organization, security, data integrity and reliability, data description and query languages will be studied within hierarchical, network, and relational models. A commercially available relational database management system will be used. May not be taken for credit by students who have received credit for CS 543. Prerequisite: CS 311.
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3.00 Credits
Declarative programming techniques: formal specification of the problem itself rather than of a solution algorithm. Survey of logic programming languages such as Prolog, applications, theoretical foundations propositional logic, predicate calculus, resolution, theorem proving, non-determinism, metaprogramming. May not be taken for credit by students who have received credit for CS 555. Enrollment Requirement: MATH 270 or 370. Prerequisite: CS 351.
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3.00 Credits
Computer arithmetic, solution of a single algebraic equation, solution of systems of equations interpolating polynomials, numerical integration, numerical solution of ordinary differential equations; error analysis and computational effort of numerical algorithms. Combines theoretical ideas with hands-on laboratory experience. Also offered as MATH 464. Students may not receive credit for both. Enrollment Requirement: CS 111 and MATH 162.
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3.00 Credits
An introduction to the objectives and techniques used by practitioners and researchers in artificial intelligence. Explores a number of aspects of computational models of intelligence including problem solving (uninformed and informed strategies), game playing, knowledge representation, reasoning, planning, natural language processing (text and speech), and learning. There will be a number of hands-on assignments that will allow the students to become familiar with the practice of building intelligence systems. Prerequisite: CS 311.
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