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Communication
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Communication Theory and Methods |
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Communication, Culture and Social Context |
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Mass Communication |
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COMM 499C - Independent Study Units: 3
May be used by students who desire to do special individualized projects with an instructor. Number of units to be decided between the student and the instructor. May be repeated for a total of six 6 units. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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Computer Information Systems |
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CIS 300 - Computer Information Fluency Units: 3
Knowledge work productivity concepts; advanced software functionality to support personal and group productivity; organization and management of data via spreadsheets and database tools; accessing organizational and external data; information search strategies; algorithmic and critical thinking; Web page design and programming; effective presentation and delivery. Enrollment Restrictions: For students matriculating prior to Fall 2018, enrollment is restricted to students who have completed the Entry-Level Mathematics (ELM) requirement. For students matriculating in Fall 2018 or later, enrollment is restricted to students in Mathematics/Quantitative Reasoning Placement Categories I and II, or who have completed MATH 101 or MATH 105 with a grade of C (2.0) or better.
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CIS 341 - Computer System Analysis and Design Units: 3
Covers the systems development life cycle, compares traditional methods of systems development to newer, emerging methods, process and data models for an information system, user interface for an information system, feasibility study and cost benefit analysis.
Prerequisite(s): CS 211 .
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CIS 444 - Web Programming Units: 3
Methods, software architecture, and standards for Internet-scale software infrastructure (services and applications). Includes foundations of the Web; distributed systems; client server architectures from 2-tier to n-tier and through Web Applications Design; and distributed object-based systems and associated technologies.
Prerequisite(s): CS 443 .
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CIS 490 - Project Management and Practice Units: 3
Advanced CIS majors operating as a high-performance team will engage in and complete the design and implementation of a significant information system. Project management, management of the CIS function, and systems integration will be components of the project experience.
Prerequisite(s): CIS 444 .
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Computer Science |
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CS 100 - Computer Basics Units: 1
Serves as an introduction to the potential of microcomputers, social, historical perspectives, word processing, spreadsheets, communications, operating systems, editors, and networking. Grading Basis: Graded Credit/No Credit. Credit may not be counted toward the computer science major.
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CS 105 - Media-Propelled Computational Thinking Units: 3
A media-propelled introduction to computation. Programming languages such as Alice, Java, Python, or Jython are studied and programming techniques are used to examine first the basic functions that draw objects, including lines and curves, and later to explore familiar physical, biological, or other scientific processes. Mathematical competence necessary for academic success will be enhanced. May not be taken for credit by students who received credit for: CS 200 -2. Enrollment Restrictions: For students matriculating prior to Fall 2018, enrollment is restricted to students who have completed the Entry-Level Mathematics (ELM) requirement. For students matriculating in Fall 2018 or later, enrollment is restricted to students in Mathematics/Quantitative Reasoning Placement Categories I and II, or who have completed MATH 101 or MATH 105 with a grade of C (2.0) or better.
Satisfies GE area: B4
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CS 111 - Computer Science I Units: 4
Emphasizes programming methodology and problem-solving. A high-level language such as C++ will be used for the specification and implementation of algorithms. Includes principles and applications of software engineering, numerical computing, artificial intelligence, databases and user interface. Students lacking basic computer literacy skills are encouraged to take CS 105 first prior to CS 111.
Prerequisite(s)/Corequisite(s): MATH 160 .
Satisfies GE area: B4
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CS 200 - Selected Topics in Computing Units: 1-3
Selected topics in computing and information technology. Credit may not be counted toward the Computer Science major. May be repeated for a total of twelve (12) units as topics change. Students should check the Class Schedule for listing of actual topics. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 211 - Computer Science II Units: 4
A continuation of program design and development. Introduction to data structures: stacks, queues, linear lists, trees, and sets. Includes pointers recursion, and implementation and analysis of sorting and searching algorithms. Extensive programming is required. Includes introduction to parallel models and algorithms, problem state space, relational database, and numerical approximation methods. Three hours of lecture. Three hours of laboratory.
Prerequisite(s): CS 111 and MATH 160 .
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CS 231 - Assembly Language and Digital Circuits Units: 4
The structure of computers, number and character representation, word and instruction formats, and flowcharting. Machine and assembly language programming, address modification, indexing, indirect addressing, subroutines, and mnemonic interpreting systems. Includes digital logic, analysis and synthesis of circuits, and circuits of commonly used computer components. Three hours of lecture
Prerequisite(s): CS 111 .
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CS 305 - Problem Solving with Java Programming Units: 3
An introduction to algorithmic and critical thinking through problem solving and Java programming. Various problems are solved through many case studies and computer solutions are produced to solve these problems through the platform of web programming on the Internet. Enrollment Restrictions: For students matriculating prior to Fall 2018, enrollment is restricted to students who have completed the Entry-Level Mathematics (ELM) requirement. For students matriculating in Fall 2018 or later, enrollment is restricted to students in Mathematics/Quantitative Reasoning Placement Categories I and II, or who have completed MATH 101 or MATH 105 with a grade of C (2.0) or better.
Satisfies GE area: BB
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CS 306 - Introduction to Computer Animation Units: 3
Introduction to the design and implementation of computer animation. The technical and creative aspects of both linear and interactive animation are investigated. Special attention is paid to the design of and production of 2-D and 3-D animations for the Internet. Enrollment Restrictions: For students matriculating prior to Fall 2018, enrollment is restricted to students who have completed the Entry-Level Mathematics (ELM) requirement. For students matriculating in Fall 2018 or later, enrollment is restricted to students in Mathematics/Quantitative Reasoning Placement Categories I and II, or who have completed MATH 101 or MATH 105 with a grade of C (2.0) or better.
Satisfies GE area: BB
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CS 331 - Computer Architecture Units: 3
A study of the functional organization and sequential operation of digital computers. The major components of a computer will be discussed. Introduction to machine instruction architecture and design. The study of the internal operations during program execution. Several computer architectures will be studied.
Prerequisite(s): CS 231 .
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CS 351 - Programming Languages Units: 3
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, and distributed and parallel programming constructs.
Prerequisite(s)/Corequisite(s): CS 311 , and MATH 270 or 370.
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CS 403 - Social and Organizational Impacts of Computing Units: 3
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 received credit for: CS 303.
Prerequisite(s): CS 311 .
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CS 421 - Theory of Computing Units: 3
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 received credit for: CS 521.
Prerequisite(s): CS 351 .
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CS 433 - Operating Systems Units: 3
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 received credit for: CS 533.
Prerequisite(s): CS 231 and CS 311 .
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CS 435 - Real-Time Concepts for Embedded Systems Units: 3
Introduction to the high-level abstract modeling concepts and the lower-level fundamental programming aspects of real-time embedded systems development. The primary focus is in the design, development and validation of microprocessor-based real-time embedded systems. Course topics will include real-time operating system design, real-time scheduling theory, general-purpose microprocessors, common bus architectures, memory management, device driver development, interrupts, general purpose peripherals: such as timers and counters, I/O subsystems along with some embedded system design problems and engineering issues.
Prerequisite(s): CS 231 and CS 311 .
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CS 436 - Introduction to Networking Units: 3
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.
Prerequisite(s): CS 311 .
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CS 441 - Software Engineering Units: 3
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 received credit for: CS 541.
Prerequisite(s): Must have passed at least two CS courses at the 400-level with a C (2.0) or better in each.
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CS 443 - Database Management Systems Units: 3
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 received credit for: CS 543.
Prerequisite(s): CS 311 .
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CS 445 - Digital Embedded Systems Design with HDL Units: 3
Concepts, technologies, and programming languages used in modern digital embedded systems. Technologies of reconfigurable computing systems such as Field Programmable Gate Arrays, design flow and implementation in reconfigurable systems, Hardware Description Languages, such as VHDL (Very high speed integrated circuits Hardware Description Language) programming. Structure and syntax of VHDL and implementation of combinatorial and sequential circuits in VHDL. Complex digital operations and subsystems implemented in dedicated hardware such as FPGAs. May not be taken for credit by students who received credit for: CS 497 -5. Cross-listed: CS 445 and EE 406 are cross-listed. Students may not receive credit for both. Two hours lecture. Two hours activity.
Prerequisite(s): CS 331 or EE 301 or PHYS 301 .
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CS 446 - Cloud Computing Units: 3
Introduction to fundamental technologies that enable cloud computing, such as software defined architectures, virtualization, and containers. Includes web middleware technologies and different levels of cloud services. Students will gain hands-on experience through developing new cloud services based on public cloud infrastructures.
Prerequisite(s): CS 443 with a minimum grade of C (2.0).
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CS 452 - Introduction to Computer Security Units: 3
Introduces students to the principles of computer security, with emphasis on applied encryption, software/system security, and web security. Subjects such as encryption algorithm, access control, authentication, buffer overflow, SQL injection and cross-site scripting attack will be covered. Both theoretical and practical knowledge will be provided to enhance understanding of computer security issues. May not be taken for credit by students who received credit for: CS 497-8.
Prerequisite(s): CS 433 .
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CS 455 - Logic Programming Units: 3
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, meta-programming. May not be taken for credit by students who received credit for: CS 555 .
Prerequisite(s): CS 351 .
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CS 464 - Numerical Analysis and Computing Units: 3
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. Cross-listed: CS 464 and MATH 464 are cross-listed. Students may not receive credit for both.
Prerequisite(s): CS 111 and MATH 162 .
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CS 471 - Introduction to Artificial Intelligence Units: 3
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. May not be taken for credit by students who received credit for: CS 571 .
Prerequisite(s): CS 311 .
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CS 473 - Artificial Neural Networks Units: 3
Theory, algorithms and applications of artificial neural networks, their applications including pattern and speech recognition, system identification, signal processing, time series prediction, financial analysis and trading. May not be taken for credit by students who received credit for: CS 573.
Prerequisite(s): CS 311 .
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CS 478 - Introduction to Deep Learning Units: 3
Introduces use or application of software to cover fundamental topics of classification, regression and clustering, and a number of corresponding learning models such as the multi-layer perceptron and its gradient-based training through the backpropagation algorithm. Fully connected neural networks will be followed by more specialized neural network architectures such as convolutional neural networks (for images), recurrent neural networks (for sequences), and memory-augmented neural networks. Recommended Preparation: MATH 374 or MATH 264 ; MATH 260 ; and MATH 342 .
Prerequisite(s): CS 311 and MATH 242 with grades of C (2.0) or better.
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CS 480 - Introduction to Optimization Units: 3
Study of Linear Programming, Goal Programming and Integer Programming. Programming methods include the simplex method and the Big M method. Theoretical aspects include optimality conditions, sensitivity analysis and duality. Cross-listed: CS 480 and MATH 480 are cross-listed. Students may not receive credit for both. Enrollment Requirement(s): CS 211 .
Prerequisite(s): MATH 374 .
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CS 481 - Introduction to Mobile Programming Units: 3
Introduces students to the fundamentals of developing applications for mobile devices including smart phones and tablets. Common issues and special consideration for programming on mobile devices will be discussed. Software engineering principles in project design and human-computer interaction will be applied. Students will also learn about the development cross-platform mobile Web applications. May not be taken for credit by students who received credit for: CS 497 -2.
Prerequisite(s): CS 351 or CIS 444 .
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CS 485 - Game Programming Units: 3
Introduction to the concepts of game development and game modeling and programming through developing playable 2D/3D games using a modern game engine. Includes the framework and roles in a team for game development, programming skills of using a game engine and modeling skills of creating 3D models with animation tools.
Prerequisite(s): CS 311 .
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CS 488 - Introduction to Internet of Things Units: 3
Concepts, technologies, applications and programming of Internet of Things (IoT). Includes resource-constrained computer systems, sensing technologies, mobile app development, security issues of IoT systems and network connectivity using low energy communication protocols such as Bluetooth Low Energy (BLE). High-level programing tools will be introduced as a way to integrate the entire system, with demonstrator applications such as a smartphone remote controlled weather station. CS 688 and CS 488 are dual-listed. The course may be taught together by the same instructor. May not be taken for credit by students who received credit for: May not be taken for credit by students who have received credit for CS 688 or CS 697-1.
Prerequisite(s): CS 311 with a minimum grade of C (2.0).
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CS 497 - Topics in Computer Science Units: 3
Introductory or advanced topics in Computer Science for undergraduate students. May be repeated as topics change for a total of six 6 units. Students should check the Class Schedule for listing of actual topics. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 498A - Individual Study in Computer Science Units: 1
Individually directed reading and study in Computer Science literature. May be repeated for a maximum of three (3) units. Enrollment Restrictions: Enrollment restricted to students with Senior standing in Computer Science. Enrollment restricted to students who have obtained consent of supervising instructor.
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CS 498B - Individual Study in Computer Science Units: 2
Individually directed reading and study in Computer Science literature. May be repeated for a maximum of three (3) units. Enrollment Restrictions: Enrollment restricted to students with Senior standing in Computer Science. Enrollment restricted to students who have obtained consent of supervising instructor.
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CS 498C - Individual Study in Computer Science Units: 3
Individually directed reading and study in Computer Science literature. May be repeated for a maximum of three (3) units. Enrollment Restrictions: Enrollment restricted to students with Senior standing in Computer Science. Enrollment restricted to students who have obtained consent of supervising instructor.
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CS 499A - Independent Research in Computer Science Units: 1
Designed for students capable of independent and original research. May be repeated for a maximum of three (3) units. Enrollment Restrictions: Enrollment restricted to students with Senior standing in Computer Science. Enrollment restricted to students who have obtained consent of supervising instructor.
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CS 499B - Independent Research in Computer Science Units: 2
Designed for students capable of independent and original research. May be repeated for a maximum of three (3) units. Enrollment Restrictions: Enrollment restricted to students with Senior standing in Computer Science. Enrollment restricted to students who have obtained consent of supervising instructor.
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CS 499C - Independent Research in Computer Science Units: 3
Designed for students capable of independent and original research. May be repeated for a maximum of three (3) units. Enrollment Restrictions: Enrollment restricted to students with Senior standing in Computer Science. Enrollment restricted to students who have obtained consent of supervising instructor.
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CS 511 - Introduction to Bioinformatics Units: 3
Application of computer technology to the management of biological information. Introduces computer algorithms that are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development. Enrollment Requirement(s): for graduate students CS 311 .
Prerequisite(s): for undergraduate students CS 311 .
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CS 512 - Introduction to Data Mining Units: 3
Illustrates the process of analyzing data from different perspectives and summarizing it into useful information so as to increase revenue, or cut costs. Introduces Data Mining software analytical tools that are used for analyzing data. Tools allow users to analyze data from many different dimensions or angles, categorize the data, and summarize the relationships identified. Enrollment Requirement(s): for graduate students CS 443 .
Prerequisite(s): for undergraduate students CS 443 .
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CS 513 - Analysis and Intractability of Algorithms Units: 3
Study of algorithms; efficient, optimal algorithms and analysis for best, worst, and average performance; computational complexity theory; algorithmic time and space bounds; levels of intractability including polynomial-time reducibility, NP-complete and NP-hard problems, and Co-NP; applications. A core course in the Computer Science M.S. program. Undergraduates must obtain consent of instructor to enroll. Enrollment Requirement(s): for graduate students: CS 311 .
Prerequisite(s): for undergraduate students CS 311 .
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CS 531 - Advanced Computer Architectures Units: 3
Comparative studies of computer system components: CPU, memory, and I/O devices; analytical modeling techniques to allow comparative evaluation of different computer architectures; multiprocessors, and array processors, vector processes multiprocessors, pipeline and super-pipeline processors, supercomputers, dataflow machines; parallelism, scalability, and programmability. Enrollment Requirement(s): for graduate students CS 331 .
Prerequisite(s): for undergraduates CS 331 .
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CS 535 - Introduction to Computer Graphics Units: 3
Introduces basic theory and programming in computer graphics. Includes graphics pipeline, rasterization, windowing and clipping, OpenGL programming, theory of domain transformations, mathematics of three-dimensional graphics involving rotation, scaling, translation and perspective projection, curve and surface modeling, lighting and shading, texture mapping, visibility algorithms, shading languages, and ray-tracing.
Prerequisite(s): CS 311 and either MATH 264 or MATH 374 with a minimum grade of C (2.0).
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CS 536 - Introduction to 3D Game Graphics Units: 3
Introduction to graphics algorithms and skills related to 3D game programming. The emphasis is on developing 3D graphics engines. Subjects covered include graphics hardware, rendering pipeline, OpenGL programming, geometric transformations, lighting and shading, texture mapping, shadowing, collision detection, animation, and other interactive computer graphics techniques. Enrollment Requirement(s): MATH 264 or MATH 374 , and for graduate students: CS 311 .
Prerequisite(s): for undergraduates CS 311 .
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CS 537 - Data Communication and Computer Networks Units: 3
Introduces TCP/IP network architecture with emphasis on upper-layer protocols and a detailed investigation into TCP and IP. It also covers local area networks, internetworking, and network programming. A core course in the Computer Science M.S. program. Undergraduates must obtain consent of instructor to enroll. Enrollment Requirement(s): for graduate students CS 436 .
Prerequisite(s): for undergraduates CS 436 .
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CS 538 - Cryptography and Network Security Units: 3
Introduction to cryptographic techniques and their applications to real-world networks security problems. Covers fundamental concepts of protecting confidentiality, end-to-end authentication, integrity and availability of information in computer systems and networks. Subjects include cryptographic methods and algorithms containing symmetric key systems, public key systems, and hash functions; computational issues in cryptography; security of wired and wireless network protocols; common network attacks and defenses.
Prerequisite(s): CS 311 with a minimum grade of C (2.0), or graduate standing in CSIS.
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CS 539 - Client/Server Computing Units: 3
State-of-the-practice on client/server computing, the key enabling technologies and their inter-relationships, development and implementation of client/server/ applications, emerging technologies that may affect the future practice within the client/server environment. Enrollment Requirement(s): for graduate students CS 441 .
Prerequisite(s)/Corequisite(s): for undergraduates CS 441 .
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CS 542 - Design Patterns and Object-Oriented Analysis Units: 3
Studies object-oriented analysis and design and their roles in software development. Many documented patterns in program designs will be introduced and analyzed. Advanced topics in software engineering such as software metrics, software architecture and software reuse are also discussed. A core course in the Computer Science M.S. program. Undergraduates must obtain consent of instructor to enroll. Enrollment Requirement(s): for graduate students CS 441 .
Prerequisite(s): for undergraduates CS 441 .
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CS 551 - Advanced Programming Languages Units: 3
Formal syntax of programming languages such as Backus-Naur form and its variations, attribute grammars, two-level grammars, formal semantics of programming languages, including operational semantics, denotational semantics, and axiomatic semantics. A core course in the Computer Science M.S. program. Undergraduates must obtain consent of instructor to enroll. Enrollment Requirement(s): for graduate students: CS 351 and CS 421 .
Prerequisite(s): for undergraduates CS 351 and CS 421 .
Prerequisite(s)/Corequisite(s): CS 421 .
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CS 553 - Compilers Units: 3
Study of lexical scanning, parsing methods, intermediate code generation, error detection, and recovery. Included will be the design and implementation of a simple compiler or components of an actual compiler. May not be taken for credit by students who received credit for: CS 453. Enrollment Requirement(s): for graduate students: CS 351 and CS 421 .
Prerequisite(s): for undergraduates: CS 351 and CS 421 .
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CS 555 - Logic Programming Units: 3
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, meta-programming. Enrollment Requirement(s): for graduate students CS 351 and MATH 270 or 370.
Prerequisite(s): for undergraduates CS 351 and MATH 270 or 370.
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CS 571 - Artificial Intelligence Units: 3
A comprehensive study of basic concepts techniques and a number of detailed algorithms used by researchers and practitioners of artificial intelligence. Subjects covered include problem-solving, knowledge representation and reasoning, planning, uncertainty reasoning and decision-making, machine-learning, and natural language processing. A core course in the Computer Science M.S. program. Enrollment Restrictions: Enrollment restricted to graduate students and to undergraduates who have obtained consent of instructor. Enrollment Requirement(s): for graduate students CS 421 .
Prerequisite(s): for undergraduates CS 421 .
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CS 572 - Artificial Intelligence and Games Units: 3
A comprehensive study of artificial intelligence techniques and their application to computer games. Analysis of the algorithms that work on a character-by-character basis. Analysis and study of an artificial intelligence-based game model split into three components: strategy, decision-making, and movement. Additionally, this course will provide the background for students interested in graphics applied to computer games development. Enrollment Requirement(s): for graduate students CS 351 .
Prerequisite(s): for undergraduates CS 351 .
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CS 574 - Intelligent Information Retrieval Units: 3
In-depth discussion of recent approaches in the field of the indexing, processing, retrieval, and ranking of textual data. Study of classic and current retrieval models, algorithms, and information retrieval system implementations. Practical applications using existing information retrieval systems. Advanced topics will address “intelligent” IR, including Natural Language Processing techniques, “smart” Web agents, and cross-linguistic information retrieval. Enrollment Requirement(s): for graduate students CS 311 .
Prerequisite(s): for undergraduates CS 311 .
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CS 575 - Machine Learning Systems Units: 3
Discusses important machine learning algorithms, systems, theory and practices including decision-tree learning, artificial neural networks, Bayesian approaches, genetic algorithms and programs, reinforcement learning, computational learning theory, etc. May not be taken for credit by students who received credit for: CS 475. Enrollment Requirement(s): for graduate students: CS 311 .
Prerequisite(s): for undergraduate students: CS 311 .
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CS 577 - Intelligent Tutoring Systems Units: 3
Study of concepts and structures necessary to design and implement intelligent tutoring systems. Comparison with non-intelligent systems. Includes knowledge representation techniques for the pedagogical model, domain model, and student model. Interface issues will be discussed. A small tutoring system will be implemented. Enrollment Requirement(s): for graduate students CS 421 .
Prerequisite(s): for undergraduates CS 421 .
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CS 578 - Introduction to Text Mining Units: 3
An introduction to the study of classical and current approaches in the field of the processing, extraction and classification of textual data. The approaches include natural language processing, statistical models of language, algorithms in machine learning use applied in text mining. Analysis of current applications in static data collections and dynamic data collections such as the web will be carried out. Enrollment Requirement(s): for graduate students CS 311 .
Prerequisite(s): for undergraduate students CS 311 .
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CS 590 - Introduction to Research and Publishing in Computer Science Units: 3
Introduces research techniques and technical writing styles in Computer Science. Designed to help graduate students prepare for their CS 698 and CS 699 course in which independent research abilities and technical writing skills are required. By passing this course, the Graduate Writing Requirement is satisfied. Enrollment Restrictions: Enrollment restricted to graduate students.
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CS 597 - Advanced Topics in Computer Science Units: 3
Advanced topics in computer science for graduate students or advanced undergraduate students. May be repeated for credit as topics change for a total of six 6 units. Students should check the Class Schedule for listing of actual topics. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 612 - Data Mining in Bioinformatics Units: 3
Introduces the Data Mining approaches suited for Bioinformatics. Shows that mining biological data helps to extract useful knowledge from massive datasets gathered in biology, and in other related life sciences areas such as medicine and neuroscience.
Prerequisite(s): CS 513 .
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CS 613 - Advanced Computational Complexity Units: 3
In-depth discussion of computational complexity theory including models of computation, polynomially bounded, NP-completeness, reducibility, and beyond NP-completeness, and intractable problems. NP-complete problems in various areas will be discussed.
Prerequisite(s): CS 513 .
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CS 614 - Algorithms in Bioinformatics Units: 3
Covers the computational models and algorithms in bioinformatics research. The topics include sequence assembly, sequence alignment, motif searching, pattern matching, DNA microarray analysis, clustering and evolutionary trees, and Hidden Markov Models. Enrollment Requirement(s): CS 311 and MATH 242 .
Prerequisite(s): CS 513 .
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CS 633 - Advanced Operating Systems Units: 3
Current research and methodology in operating systems for operating system designers. Advance study includes topics of synchronization, deadlock, virtual memory, security, distributed systems and control, and modeling and analysis. Enrollment Requirement(s): CS 433 .
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CS 635 - Advanced Computer Graphics Units: 3
Covers advanced concepts and methods of three-dimensional computer graphics. Studies the recent developments in rendering, modeling, animation, and visualization. Provides students with sufficient background to write advanced computer graphics applications.
Prerequisite(s): CS 535 or CS 536 .
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CS 637 - Advanced Computer Networks Units: 3
Broadband integrated services digital networks, high-speed networks, radio and satellite networks, lightwave networks; multimedia communications, wireless communications, high-speed communications; network design, network architectures, traffic and admission control, routing and flow control, performance issues, traffic characteristics. Enrollment Requirement(s): CS 433 .
Prerequisite(s): CS 537 .
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CS 643 - Advanced Database Management Systems Units: 3
Advanced data models such as object-oriented databases, distributed databases, deductive databases, and multimedia databases, abstractions, dependencies, normalizations, query optimizations, implementations, languages, database machines, and other advanced topics.
Prerequisite(s): CS 443 .
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CS 673 - Artificial Neural Networks and Forecasting Units: 3
Includes forecasting using statistical methods such as Box-Jenkins ARIMA models for time series analysis and forecasting with artificial neural networks. Applications include financial forecasting for stock prices, commodity trading volumes, or currency exchange rates, and other forecasting such as electric load, ocean temperature, river flow volume, and traffic flow. Current state-of-art forecasting methodologies from journals, conference proceedings, and books will be discussed.
Prerequisite(s): CS 571 .
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CS 677 - Development of Intelligent Tutoring Systems Units: 3
Study of issues related to design, implementation and evaluation of intelligent tutoring systems. Students will work in teams to develop tutoring systems and produce plans to evaluate these systems.
Prerequisite(s): CS 571 .
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CS 678 - Text Mining Units: 3
In-depth discussion of selected subjects in Text Mining with emphasis on the design, implementation and testing of approaches and algorithms in the field. Approaches and algorithms included are the following: Finite-state Automata, Hidden Markov Models, Support Vector Machines, and Conditional Random Fields.
Prerequisite(s): CS 571 .
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CS 688 - Advanced Internet of Things Units: 3
Concepts, technologies, applications and programming of Internet of Things (IoT). Includes review of current challenges and recent advances in IoT field, resource-constrained computer systems, sensing technologies, edge computing, cloud computing, mobile app development, security issues of IoT systems and network connectivity using low energy communication protocols such as Bluetooth Low Energy (BLE). Advanced high-level programming tools will be used to integrate the entire system, with demonstrator applications such as a smartphone remote controlled weather station. CS 488 and CS 688 are dual-listed. The courses may be taught together by the same instructor. May not be taken for credit by students who received credit for: CS 488 or CS 697-1.
Prerequisite(s)/Corequisite(s): CS 537 .
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CS 696A - Graduate Individual Study in Computer Science Units: 1
Individually directed reading and study in Computer Science literature for graduate students, focusing on advanced topics. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 696B - Graduate Individual Study in Computer Science Units: 2
Individually directed reading and study in Computer Science literature for graduate students, focusing on advanced topics. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 696C - Graduate Individual Study in Computer Science Units: 3
Individually directed reading and study in Computer Science literature for graduate students, focusing on advanced topics. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 697 - Graduate Topics in Computer Science Units: 3
Advanced topics of current interest in computer science for graduate students. Students should check the Class Schedule for listing of actual topics. May be repeated for credit as topics change for a total of six 6 units. Enrollment Restrictions: Enrollment restricted to students who have obtained consent of instructor.
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CS 698 - Master’s Research Project Units: 3
Faculty-supervised investigation, to culminate in a written report for the master’s degree. It may be repeated, but only three (3) units count toward the master’s degree. Grading Basis: Graded Credit/No Credit. Enrollment Requirement(s): An officially appointed advisory committee with a project advisor and advancement to candidacy.
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CS 699A - Master’s Thesis Units: 1
Preparation of a thesis for the master’s degree. May be repeated but only six 6 units count toward the master’s degree. Grading Basis: Credit/No Credit. Enrollment Requirement(s): An officially appointed thesis committee with a thesis advisor as the chair of the committee and advancement to candidacy.
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CS 699B - Master’s Thesis Units: 2
Preparation of a thesis for the master’s degree. May be repeated but only six 6 units count toward the master’s degree. Grading Basis: Credit/No Credit. Enrollment Requirement(s): An officially appointed thesis committee with a thesis advisor as the chair of the committee and advancement to candidacy.
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CS 699C - Master’s Thesis Units: 3
Preparation of a thesis for the master’s degree. May be repeated but only six 6 units count toward the master’s degree. Grading Basis: Credit/No Credit. Enrollment Requirement(s): An officially appointed thesis committee with a thesis advisor as the chair of the committee and advancement to candidacy.
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CS 700A - Thesis Extension Units: 1
Registration is limited to students who have received a grade of Satisfactory Progress (SP) in CS 699 and who expect to use the facilities and resources of the University to work on or complete the thesis. Also, students must be registered in CS 700 when the completed thesis is granted final approval. May be repeated for a total of three (3) units, but credit will not be counted toward the Master of Science in Computer Science. Grading Basis: Graded Credit/No Credit.
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CS 700B - Thesis Extension Units: 2
Registration is limited to students who have received a grade of Satisfactory Progress (SP) in CS 699 and who expect to use the facilities and resources of the University to work on or complete the thesis. Also, students must be registered in CS 700 when the completed thesis is granted final approval. May be repeated for a total of three (3) units, but credit will not be counted toward the Master of Science in Computer Science. Grading Basis: Graded Credit/No Credit.
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CS 700C - Thesis Extension Units: 3
Registration is limited to students who have received a grade of Satisfactory Progress (SP) in CS 699 and who expect to use the facilities and resources of the University to work on or complete the thesis. Also, students must be registered in CS 700 when the completed thesis is granted final approval. May be repeated for a total of three (3) units, but credit will not be counted toward the Master of Science in Computer Science. Grading Basis: Graded Credit/No Credit.
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Convergent Journalism |
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CJRN 401A - Convergent Journalism Practicum Units: 1
Provides support for reporting, editorial, and leadership positions in campus student news outlets (e.g., the student newspaper, hard copy and online) and provides opportunities to apply advanced skills in convergent journalism, with special emphasis on producing convergent content for student news outlets. May be repeated for credit for a total of nine (9) units. Grading Basis: Graded Credit / No Credit.
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CJRN 401B - Convergent Journalism Practicum Units: 2
Provides support for reporting, editorial, and leadership positions in campus student news outlets (e.g., the student newspaper, hard copy and online) and provides opportunities to apply advanced skills in convergent journalism, with special emphasis on producing convergent content for student news outlets. May be repeated for credit for a total of nine (9) units. Grading Basis: Graded Credit / No Credit.
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CJRN 401C - Convergent Journalism Practicum Units: 3
Provides support for reporting, editorial, and leadership positions in campus student news outlets (e.g., the student newspaper, hard copy and online) and provides opportunities to apply advanced skills in convergent journalism, with special emphasis on producing convergent content for student news outlets. May be repeated for credit for a total of nine (9) units. Grading Basis: Graded Credit / No Credit.
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Cultural Competency in Healthcare |
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CCHC 500 - Clinical Care and Cultural Competency Units: 2
Explores how cultural backgrounds of patients and providers impact the healthcare encounter. Examines how clinical healthcare settings and organizations can act as barriers to providing effective services to diverse communities. Reviews standards, laws, and accreditation mandates relevant to the health care of culturally- and linguistically diverse communities.
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CCHC 510 - Special Populations and Health Care Units: 2
Examines the ways in which special populations are defined, their access to care, and questions of health equity. Covers major issues influencing health services and delivery to special populations, focusing on disparities and strategies to address healthcare needs. Focus includes special populations’ service provision, advocacy, patient/client-centered care, social aspects of disease and wellness, health promotion, and education. Reviews history of health and social welfare programs. Examines social and environmental determinants of health as well as the health service needs of special population.
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CCHC 520 - Ethics and Culture in Medicine Units: 2
Reviews the concepts, principles, and methods of medical ethics, emphasizing issues of cultural difference, identity, and cross-cultural translation. Examines mainstream ethical principles through case studies involving diverse cultural settings, belief systems, and moral traditions. Themes include practitioner-patient communication, informed consent, end-of-life issues, family dynamics, standards of medical decision-making, normative concepts of medicine, appropriate treatment, and ethical intervention and care.
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CCHC 530 - Cross Cultural Health Communication Units: 2
Examines how language and communication impact delivery of health care services to culturally- and linguistically-diverse communities. Reviews standards, policies, and accreditation mandates impacting language access. Focuses on strategies for cross-cultural communication, effective ways to ensure language access, and health literacy for diverse communities.
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CCHC 540 - Palliative Care in Diverse Communities Units: 2
Explores palliative care and end-of-life issues as manifested in culturally-diverse communities. Examines how diverse communities perceive, use, and assess palliative care. Addresses barriers to palliative care in relation to language, social, and cultural needs, and introduces best practices to improve access and utilization of services.
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CCHC 550 - Practicing Cultural Competency in Health Care Units: 2
Covers the design, delivery, and evaluation of strategies that promote cultural competence and increase health promotion and illness prevention in diverse communities. Concepts of community assessment, program planning, and illness prevention are applied to develop a cultural competency plan for a particular area of the healthcare system.
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Dance |
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DNCE 101 - Introduction to Dance Units: 3
Survey of dance on the stage and off, in the studio as well as in the club, and performed by everyday and famous people. Focusing primarily on movement in the United States, investigates dance as a cultural and historical phenomenon. Course includes: lectures, demonstrations, dance performances, research papers, and collaborative presentations.
Satisfies GE area: C1
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DNCE 124 - Introduction to Dance Through Film Units: 3
Lecture course that surveys various genres of dance through classic, contemporary, and experimental films and videos. A range of documentary, dance-for-the-camera, and popular culture works that offer diverse perspectives on dance and cultural identity will be viewed.
Satisfies GE area: C1
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DNCE 130 - Topics in Dance Practice Units: 1-3
Studio practice in various movement genres challenge and awaken students physically and artistically. Subjects may include Ballroom, Salsa, Latin, Capoeira, Ballet, Jazz, Somantics, West African, Hula, Butoh, etc. Depending on units, course may also include quizzes, papers, and performances. May be repeated for a total of eight (8) units.
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DNCE 200 - Movement Awareness Units: 3
Investigates functional movement through internal observation alongside dance improvisation to enhance spontaneous creativity and artistic research. Open to all levels of abilities. Course assignments focus on ways to articulate sensorial observations through written response papers and projects that focus on the body and cultural identity. May not be taken for credit by students who received credit for: DNCE 130 -1.
Satisfies GE area: C1
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DNCE 201 - Contemporary Dance Technique I Units: 3
Studio course focusing on alignment and dance phrases alongside composition and improvisation. Practice will increase strength, flexibility, and body awareness, and also investigate choreographic theories of dance based on diverse approaches to contemporary dance. Includes guest artists, live performances, and research paper/projects. May be repeated for a total of six 6 units. One hour lecture and three hours studio work.
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