Close Menu

Course Descriptions

Undergraduate

CS 100 Introduction to the Profession

An introduction to science and engineering as a profession. Examines the problem-solving process used in engineering and science. Emphasizes the interdisciplinary and international nature of problem-solving and the need to evaluate solutions in terms of a variety of constraints: computational, financial, and social. 1-2-2 (C)
» Sample Syllabus

CS 104 Introduction to Computer Programming for Engineers

Introduces the use of high-level programming language as a problem-solving tool in engineering including basic data structures and algorithms, structured programming techniques, and software documentation. Designed for students who have had little or no prior experience with computer programming. Must be enrolled in one of the following Majors: Aerospace Engineering, Applied Mathematics, Architectural Engineering, Civil Engineering, Chemical Engineering, Engineering Management, Mechanical Engineering, Materials Science and Engineering. 2-1-2

CS 105 Introduction to Computer Programming

Introduces the use of high-level programming language as a problem-solving tool, including basic data structures and algorithms, structured programming techniques, and software documentation. Designed for students who have had little or no prior experience with computer programming. May not be enrolled in one of the following majors: Aerospace Engineering, Applied Mathematics, Computer Information Systems, Computer Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, Materials Science and Engineering. 2-1-2

CS 110 Computing Principles

An introduction to the following "big ideas" of computer science: (1) computing is a creative activity; (2) abstraction reduces information and detail to facilitate focus on relevant concepts; (3) data and information facilitate the creation of knowledge; (4) algorithms are used to develop and express solutions to computational problems; (5) programming enables problem solving, human expression, and creation of knowledge; (6) the internet pervades modern computing; and (7) computing has global impacts. 2-0-2

CS 115 Object-Oriented Programming I

Introduces the use of a high-level object-oriented programming language as a problem-solving tool, including basic data structures and algorithms, object-oriented programming techniques, and software documentation. Designed for students who have had little or no prior experience with computer programming. For students in CS and CS-related degree programs. 2-1-2
» Sample Syllabus

CS 116 Object-Oriented Programming II

Introduces more advanced elements of object-oriented programming, including dynamic data structures, recursion, searching and sorting, and advanced object-oriented programming techniques. For students in CS and CS-related degree programs. Prerequisite: CS 115 (minimum grade of C). 2-1-2
» Sample Syllabus

CS 201 Accelerated Introduction to Computer Science

Introduces more advanced elements of object-oriented programming, including dynamic data structures, recursion, searching and sorting, and advanced object-oriented programming techniques. For students in CS and CS-related degree programs. Prerequisite: CS 105 or CS 115. 3-2-4

CS 330 Discrete Structures

Introduction to the use of formal mathematical structures to represent problems and computational processes. Topics covered include Boolean algebra, first-order logic, recursive structures, graphs, and abstract language models. Corequisite: CS 116 or CS 201. Credit will not be granted for both CS 330 and MATH 230. 3-1-3

CS 331 Data Structures and Algorithms

Implementation and application of the essential data structures used in computer science. Analysis of basic sorting and searching algorithms and their relationship to these data structures. Particular emphasis is given to the use of object-oriented design and data abstraction in the creation and application of data structures. Prerequisite: CS 116 or CS 201. 2-2-3

CS 350 Computer Organization and Assembly Language Programming

Introduction to the internal architecture of computer systems-including micro-, mini-, and mainframe computer architectures. Focuses on the relationship among a computer's hardware, its native instruction set, and the implementation of high-level languages on that machine. Uses a set of assembly language programming exercises to explore and analyze a microcomputer architecture. Prerequisite: CS 116 or CS 201. Credit will not be granted for both CS 350 and ECE 242. 2-2-3 (C)

CS 351 Systems Programming

Examines the components of sophisticated multilayer software systems, including device drivers, systems software, applications interfaces, and user interfaces. Explores the design and development of interrupt-driven and event-driven software. Prerequisites: CS 331 and (CS 350 or ECE 242). 2-2-3

CS 397 Special Projects

Instructor permission required. Credit: 1 to 6 hours.

CS 401 Introduction to Advanced Studies I

First course in a two-course sequence that is designed to prepare students for graduate study in computer science. Explores the implementation and application of fundamental data structures and algorithms with an emphasis on object-oriented programming in Java. Examines the relationship between these elements and the mathematical structures that form the foundation of computer science. This course does not apply toward master's or Ph. D. credit in Computer Science. Prerequisite: CS 200 or CS 201. 2-2-3
» Sample Syllabus

CS 402 Introduction to Advanced Studies II

Second course in a two-course sequence that is designed to prepare students for graduate study in computer science. Explores the development of the multiple layers of software that form a sophisticated software system, from device drivers to application interfaces to user interfaces. Examines how computer architecture influences software development. Emphasizes the design and implementation of interrupt-driven/event-driven software. This course does not apply toward master's or Ph. D. credit in Computer Science. Prerequisite: CS 401. 2-2-3

CS 411 Computer Graphics

Overview of display devices and applications. Vector graphics in two and three dimensions. Image generation, representation, and manipulation. Homogeneous coordinates. Modeling and hidden line elimination. Introduction to raster graphics. Perspective and parallel projections. Prerequisite: CS 331, CS 401, or CS 403. 3-0-3 (T)

CS 422 Data Mining

This course will provide an introductory look at concepts and techniques in the field of data mining. After covering the introduction and terminologies to Data Mining, the techniques used to explore the large quantities of data for the discovery of meaningful rules and knowledge such as market basket analysis, nearest neighbor, decision trees, and clustering are covered. The students learn the material by implementing different techniques throughout the semester. Prerequisites: CS 331, CS 401, or CS 403. 3-0-3 (C) (T)

CS 425 Database Organization

Overview of database architectures, including the Relational, Hierarchical, Network, and Object Models. Database interfaces, including the SQL query language. Database design using the Entity-Relationship Model. Issues such as security, integrity, and query optimization. Prerequisite: CS 331, CS 401, or CS 403. 3-0-3 (C) (T)

CS 429 Information Retrieval

Overview of fundamental issues of information retrieval with theoretical foundations. The information-retrieval techniques and theory, covering both effectiveness and run-time performance of information-retrieval systems are covered. The focus is on algorithms and heuristics used to find documents relevant to the user request and to find them fast. The course covers the architecture and components of the search engine such as parser, stemmer, index builder, and query processor. The students learn the material by building a prototype of such a search engine. Prerequisites: CS 331 or CS 401; requires strong programming knowledge. 3-0-3 (C) (T)

CS 430 Introduction to Algorithms

Introduction to the design, behavior, and analysis of computer algorithms. Searching, sorting, and combinatorial algorithms are emphasized. Worst case and average bounds on time and space usage. Prerequisites: (CS 330 and CS 331), or (CS 331 and MATH 230), or CS 401, or CS 403. 3-0-3 (C) (T)

CS 440 Programming Languages and Translators

Study of commonly used computer programming languages with an emphasis on precision of definition and facility in use. Scanning, parsing, and introduction to compiler design. Use of compiler generating tools. Prerequisites: CS 331 and (CS 330 or MATH 230), or CS 401, or CS 403. 3-0-3 (T)

CS 442 Mobile Applications Development

Students will learn a variety of software engineering techniques and design patterns to assist in the rapid development and prototyping of applications, leveraging frameworks and APIs provided by current mobile development platforms (such as Android and iOS). Application lifecycles, data management and persistence mechanisms, and user interface design, among other topics, will be covered. Industry speakers will be invited to speak about best practices. Students (individually or in teams) will take ideas from concept to final implementation and will present their work at the end of the semester. When appropriate, students may take the additional step of deploying their work on the appropriate application marketplace(s). Prerequisites: (CS 331 or CS 401) and (CS 351 or CS 402). (CS 351 and CS 402 may be taken concurrently.) 3-0-3 (T)

CS 443 Compiler Construction

This course covers the design and implementation of a compiler for modern languages by implementing the following: abstract syntax trees, intermediate representations, static analysis, fix-point operations, symbol tables and type checking, and first-order and high-order function implementation. Students will incrementally create a series of compilers. Prerequisite: CS 440 (minimum grade of D). 3- 0- 3.

CS 445 Object-Oriented Design and Programming

Introduction to methodologies for object-oriented design and programming. Examines the object model and how it is realized in various object-oriented languages. Focuses on methods for developing and implementing object-oriented systems. Prerequisite: CS 331, CS 401, or CS 403. 3-0-3 (T)

CS 447 Distributed Objects

This course provides an introduction to architecture, analysis, design, and implementation of distributed, multi-tier applications using distributed object technology. The course focuses on the services and facilities provided by an Object Request Broker (ORB). Students will use a commercially available ORB and Database Management System to develop distributed object applications. Prerequisite: CS 445. 3-0-3 (C) (T)

CS 450 Operating Systems

Introduction to operating system concepts-including system organization for uniprocessors and multiprocessors, scheduling algorithms, process management, deadlocks, paging and segmentation, files and protection, and process coordination and communication. Prerequisites: (CS 351 or CS 401) and CS 402, or CS 403. 3-0-3 (T)

CS 451 Introduction to Parallel and Distributed Computing

This course covers general introductory concepts in the design and implementation of parallel and distributed systems, covering all of the major branches such as Cloud Computing, Grid Computing, Cluster Computing, Supercomputing, and Many-Core Computing. Prerequisite: CS 450. 3-0-3.

CS 455 Data Communications

Introduction to data communication concepts and facilities with an emphasis on protocols and interface specifications. Focuses on the lower four layers of the ISO-OSI reference model. Prerequisite: CS 450. 3-0-3 (T)

CS 456 Introduction to Wireless Networks and Performance

This class provides an opportunity for students to obtain a fundamental understanding of the nature and operation of the full range of wireless networks (personal, local area, wide area, and satellite) and their performance characteristics, future potential, and challenges through class lectures, assigned readings, homework, projects, and various hands-on experiences. Prerequisites: (CS 350 or ECE 242 or (CS 401 and CS 402) or CS 403). 3-0-3 (T)

CS 458 Information Security

An introduction to the fundamentals of computer and information security. This course focuses on algorithms and techniques used to defend against malicious software. Topics include an introduction to encryption systems, operating system security, database security, network security, system threats, and risk avoidance procedures. Prerequisites: CS 425 and CS 450. 3-0-3 (C) (T)

CS 470 Computer Architecture

Introduction to the functional elements and structures of digital computers. Detailed study of specific machines at the register transfer level illustrates arithmetic, memory, I/O and instruction processing. Prerequisites: (CS 350 or ECE 242) and ECE 218. 2-2-3 (T) (C)

CS 480 Artificial Intelligence: Planning and Control

Introduction to computational methods for intelligent control of autonomous agents, and the use of programming paradigms that support development of flexible and reactive systems. These include heuristic search, knowledge representation, constraint satisfaction, probabilistic reasoning, decision-theoretic control, and sensor interpretation. Particular focus will be places on real-world application of the material. Prerequisite: (CS 331 or CS 401 or CS 403) and MATH 474 . (MATH 474 may be taken concurrently.). 3-0-3 (T)

CS 481 Artificial Intelligence: Language Understanding

Theory and programming paradigms that enable systems to understand human language texts and extract useful information and knowledge. F5example, extraction of structured event representations from news stories or discovering new research hypotheses by analyzing thousands of medical research articles. the course covers a variety of text analysis and text mining methods, with an emphasis on building working systems. Connections to information retrieval, data mining, and speech recognition will be discussed. Prerequisites: (CS 331 or CS 401 or CS 403) and MATH 474. 3-0-3 (T)

CS 482 Information and Knowledge Management Systems

This capstone course is designed as a project course whose purpose is to enable students to see how the various algorithms and systems they have learned about in their prerequisite courses can be used in context to create useful knowledge management tools. Class periods will be divided among discussion of design of information and knowledge management systems, lectures on effective project management techniques, and hands-on advising of student project group meetings. Prerequisites: (CS 422 and CS 425 and CS 429) or (CS 422 and CS 425 and CS 481) or (CS 425 and CS 429 and CS 481). 3-0-3 (C) (T)

CS 485 Computers and Society

Discussion of the impact of computer technology on present and future society. Historical development of the computer. Social issues raised by cybernetics. Prerequisites: COM 421 or COM 428. 3-0-3 (C)

CS 487 Software Engineering I

Study of the principles and practices of software engineering. Topics include software quality concepts, process models, software requirements analysis, design methodologies, software testing and software maintenance. Hands-on experience building a software system using the waterfall life cycle model. Students work in teams to develop all life cycle deliverables: requirements document, specification and design documents, system code, test plan, and user manuals. Prerequisites: (CS 331 or CS 401 or CS 403) and CS 425. 3-0-3 (C) (T)
» Sample Syllabus

CS 491 Undergraduate Research

Instructor permission required. Credit: 1 to 6 hours.

CS 495 Topics in Computer Science

This course will treat a specific topic, varying from semester to semester, in which there is particular student or staff interest. Prerequisite: Instructor consent. Credit: 1 to 6 hours.

CS 497 Special Projects

Credit: 1 to 20 hours.

Graduate

CS 511 Topics in Computer Graphics

Covers advanced topics in computer graphics. The exact course contents may change based on recent advances in the area and the instructor teaching it. Possible topics include: Geometric modeling, Subdivision surfaces, Procedural modeling, Warping and morphing, Model reconstruction, Image based rendering, Lighting and appearance,Texturing, Natural phenomena, Nonphotorealistic rendering Particle systems, Character animation, Physically based modeling and animation. Prerequisite: CS 411. 3-0-3

CS 512 Topics in Computer Vision

Introduction to fundamental topics in computer vision and the application of statistical estimation techniques to this area. Intended to give the student a good basis for work in this important field. Topics include: Feature extraction, Probabilistic modeling, Camera calibration, Epipolar geometry, Statistical estimation, Model reconstruction, Statistical filtering, Motion estimation, Recognition, Shape from single image cues. Prerequisite: CS 430. 3-0-3
» Sample Syllabus

CS 513 Geospatial Vision and Visualization

Geospatial information has become ubiquitous in everyday life as evidenced by on-line mapping services such as NOKIA Here Map, Microsoft Bing Map, the “place” features on social network websites such as Facebook, and navigation apps on smart phones. Behind the scenes is digital map content engineering that enables all types of location-based services. Course material will be drawn from the instructor's research and development experience at NOKIA Location and Commerce (formerly NAVTEQ), the Chicago-based leading global provider of digital map, traffic, and location data. This course will provide a comprehensive treatment of computer vision, image processing and visualization techniques in the context of digital mapping, global positioning and sensing, next generation map making, and three-dimensional map content creations. Real world problems and data and on-site industry visits will comprise part of the course curriculum. 3-0-3
» Sample Syllabus

CS 520 Data Integration, Warehousing, and Provenance

This course introduces the basic concepts of data integration, data warehousing, and provenance. Students will learn how to query and integrate data with diverse structure (heterogeneous data) from autonomous sources using data integration, data warehousing, and Big Data analytics paradigms and systems. We will focus both on the formal underpinnings (such as schema mapping languages and the dimensional data model) as well as their practical application (e.g., developing an ETL workflow with rapid miner and creating a mapping between two example schemata). Prerequisite: CS 425. 3-0-3. Note: The previous version of this course, Database Design and Engineering, is no longer being offered.
» Sample Syllabus

CS 521 Object-Oriented Analysis and Design

This course describes a methodology that covers a wide range of software engineering techniques used in system analysis, modeling and design. These techniques integrate well with software process management techniques and provide a framework for software engineers to collaborate in the design and development process. The methodology features the integration of concepts, including software reusability, frame works, design patterns, software architecture, software component design, use-case analysis, event-flow analysis, event-message analysis, behavioral-life cycle analysis, feature, multiple-product, risk and rule analysis, and automatic code generation. (Credit will not be given for CS 521 if CS 751 is taken.) Prerequisite: CS 445 or CS 487. 3-0-3
» Sample Syllabus

CS 522 Data Mining

Continued exploration of data mining algorithms. More sophisticated algorithms such as support vector machines will be studied in detail. Students will continuously study new contributions to the field. A large project will be required that encourages students to push the limits of existing data mining techniques. Prerequisite: CS 422. 3-0-3
» Sample Syllabus

CS 525 Advanced Database Organization

Comprehensive coverage of the problems involved in database system implementation and an in-depth examination of contemporary structures and techniques used in modern database management systems. Teaches advanced skills appropriate for DBMS architects and developers, database specialist, and the designers and developers of client/server and distributed systems. Focus is on transaction management, database structures and distributed processing. Prerequisite: CS 425. 3-0-3
» Sample Syllabus

CS 529 Information Retrieval

The course covers the advanced topics in Information Retrieval. The topics such as Summarization, cross-lingual, Meta-Search, Question Answering, Parallel and distributed IR systems are discussed. The students get involved in research ideas, and get involved in individual and group projects. Prerequisite: CS 429. 3-0-3
» Sample Syllabus

CS 530 Theory of Computation

Computability topics such as Turing machines, nondeterministic machines, undecidability, and reducibility. Computational complexity topics such as time complexity, NP-completeness and intractability, time and space hierarchy theorems. Introduces the complexity classes P, NP, NL, L, PSPACE, NC, RNC, BPP and their complete problems. Prerequisite: CS 430. 3-0-3

CS 531 Topics in Automata Theory

Topics selected from mathematical systems and automata theory, decision problems, realization and minimization, algebraic decomposition theory and machines in a category. 3-0-3

CS 533 Computational Geometry

This course covers fundamental algorithms and data structures for convex hulls, Voronoi diagrams, Delauney triangulation, Euclidean spanning trees, point location, and range searching. Also included are lower bounds and discrepancy theory. Optimization in geometry will be covered. This includes fixed dimensional linear programming and shortest paths. Graphic data structures such as BSP trees will be covered. Prerequisite: CS 430. 3-0-3
» Sample Syllabus

CS 535 Design and Analysis of Algorithms

Design of efficient algorithms for a variety of problems, with mathematical proof of correctness and analysis of time and space requirements. Topics include lower bounds for sorting and medians, amortized analysis of advanced data structures, graph algorithms (strongly connected components, shortest paths, minimum spanning trees, maximum flows and bipartite matching) and NP-Completeness. Prerequisite: CS 430. 3-0-3
» Sample Syllabus

CS 536 Science of Programming

Formal specification of how programs execute operational semantics, how mathematical functions programs compute denotational semantics, and how to use logic to characterize properties and invariants of the program execution (axiomatic semantics). Prerequisite: CS 331 or CS 401. 3-0-3
» Sample Syllabus

CS 537 Software Metrics

Theoretical foundations for software metrics. Data collection. Experimental design and analysis. Software metric validation. Measuring the software development and maintenance process. Measuring software systems. Support for metrics. Statistical tools. Setting up a measurement program. Application of software measurement. Prerequisite: CS 487. 3-0-3
» Sample Syllabus

CS 538 Combinatorial Optimization

Linear programs and their properties. Efficient algorithms for linear programming. Network flows, minimum cost flows, maximum matching, weighted matching, matroids. Prerequisites: CS 430 and a linear algebra course. 3-0-3
» Sample Syllabus

CS 539 Game Theory: Algorithms and Applications

This course focuses on computational issues in the theory of games, economics, and network design. Interest in the algorithmic aspects of games is motivated by the computational issues of fundamental aspects of games and economic theory, e.g., Nash equilibrium and market equilibrium. Computing and approximating Nash equilibrium will be studied. Of considerable interest to the computer science community are problems that arise from the Internet and computer networks and are similar to issues that arise in traditional transport networks, e.g., Wardrop equilibrium. Prerequisite: CS 430 or CS 530. 3-0-3

CS 540 Foundations of Programming Language Design

The basic motivations and philosophy underlying the applications of semantic techniques in programming language theory. The structures used in semantics and the techniques that have been developed for relating various approaches to the semantics of programming languages. Prerequisite: CS 440. 3-0-3. Note: The former version of this course, Syntactic Analysis of Programming Languages, is no longer being offered.
» Sample Syllabus

CS 541 Topics in Compiler Construction

Advanced topics in compiler construction, including incremental and interactive compiling, error correction, code optimization, models of code generators, etc. The objective of the course is to provide an in-depth coverage of compiler optimization techniques, including both classical optimization and areas of current interest in compiler research. Prerequisite: CS 440. 3-0-3

CS 542 Computer Networks I: Fundamentals

This course focuses on the engineering and analysis of network protocols and architecture in terms of the Internet. Topics include content distribution, peer-to-peer networking, congestion control, unicast and multicast routing, router design, mobility, multimedia networking quality of service, security and policy-based networking. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CS 544 Computer Networks II: Network Services

Qualitative and quantitative analysis of networks. A combination of analytical and experimental analysis techniques will be used to study topics such as protocol delay, end-to-end network response time, intranet models, Internet traffic models, web services availability, and network management. Prerequisite: CS 542 or ECE 545. Graduate status required. 3-0-3
» Sample Syllabus

CS 545 Distributed Computing Landscape

Introduction to the theory of concurrent programming languages. Topics include formal models of concurrent computation such as process algebras, nets, and actors; high-level concurrent programming languages and their operational semantics; and methods for reasoning about correctness and complexity of concurrent programs. Prerequisite: CS 450. Graduate status required. 3-0-3
» Sample Syllabus

CS 546 Parallel and Distributed Processing

This course covers general issues of parallel and distributed processing from a user's point of view, which include system; programming, performance evaluation, and application issues of parallel and distributed computers, and the influence of communication and parallelism on algorithm design. Prerequisite: CS 430 and CS 450. Graduate status required. 3-0-3

CS 547 Wireless Networking

This course introduces cellular/PCS systems, short-range mobile wireless systems, fixed wireless systems, satellites, and ad hoc wireless systems. It explains in detail the underlying technology as well regulations, politics, and business of these wireless communications systems. It looks beyond the hype, examining just what is and is not possible with present-day and future wireless systems. As an advanced graduate course, it will combine extensive reading and in class discussion of the research literature with in-dept independent research projects of students' own choosing. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CS 548 Broadband Networks

The course studies the architectures, interfaces, protocols, technologies, products and services for broadband (high-speed) multimedia networks. The key principles of the protocols and technologies used for representative network elements and types of broadband network are studied. Specifically, cable modems, Digital Subscriber Lines, Power Lines, wireless 802.16 (WiMax), and broadband cellular Internet are covered for broadband access; for broadband Local Area Networks (LANs), Gigabit Ethernet, Virtual LANs and wireless LANs (802.11 WiFi and Bluetooth) are discussed; for broadband Wide Area Networks (WANs) the topics covered include optical networks (SONET/SDH,DWDM, optical network nodes, optical network nodes, optical switching technologies), frame-relay, ATM, wire-speed routers, IP switching, and MPLS. Also, quality of service issues in broadband networks and a view of the convergence of technologies in broadband networks are covered. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CS 549 Cryptography and Network Security

This course provides an introduction to the theory and practice of cryptography and network security. The course covers conventional encryption such as classical encryption techniques, modern encryption techniques and encryption algorithms. Students are introduced to the basic number theory, which is used as the foundation for public-key encryption. The public-key cryptography such as encryption methods and digital signatures is covered. Message authentication and hash functions are also discussed. Students will learn techniques of key management, secret sharing and conducting interactive proofs. In addition, the practical network and security protocols are discussed. Prerequisite: CS 430. 3-0-3
» Sample Syllabus

CS 550 Advanced Operating Systems

Advanced operating system design concepts, such as multimedia OS, multiprocessor systems, virtual memory management, process migration, process scheduling, synchronization, file systems. Study of systems highlighting these concepts. Prerequisite: CS 450. 3-0-3
» Sample Syllabus

CS 551 Operating System Design and Implementation

This course covers in detail the design and implementation of processes, interprocess communication, semaphores, monitors, message passing, remote procedure calls, scheduling algorithm, input/output, device drivers, memory management, file system design, network file servers, atomic transactions, security and protection mechanisms. The hardware-software interface is examined in detail. Students modify and extend a multiuser operating system. Prerequisite: CS 450. 3-0-3
» Sample Syllabus

CS 552 Distributed Real-Time Systems

With the advancement of computer hardware, embedded devices, and network technology, real-time applications have become pervasive, ranging from smart automobiles to automated traffic control. Different from general-purpose applications, correct executions of real-time applications depend on both functional correctness and temporal correctness. This course is to study the fundamentals of distributed real-time computing with the focus on its temporal aspects. Prerequisite: CS 450. 3-0-3
» Sample Syllabus

CS 553 Cloud Computing

This course is a tour through various topics and technologies related to cloud computing. Students will explore solutions and learn design principles for building large network-based systems to support both compute-intensive and data-intensive applications across geographically distributed infrastructure. Topics include resource management, programming models, application models, system characterizations, and implementations. Discussions will often be grounded in the context of deployed cloud computing systems such as Amazon EC2 and S3, Microsoft Azure, Google AppEngine, Eucalyptus, Nimbus, OpenStack, Google's MapReduce, Yahoo's Hadoop, Microsoft's Dryad, Sphere/Sector, and many other systems. The course involves lectures, outside invited speakers, discussions of research papers, programming assignments, and a major project (including both a written report and an oral presentation). Prerequisite: CS 450 or CS 455. 3-0-3

CS 554 Data-Intensive Computing

This course is a tour through various research topics in distributed data-intensive computing, covering topics in cluster computing, grid computing, supercomputing, and cloud computing. We will explore solutions and learn design principles for building large network-based computational systems to support data intensive computing. This course is geared for junior/senior level undergraduates and graduate students in computer science. Prerequisite: CS 450. 3-0-3

CS 555 Analytic Models and Simulation of Computer Systems

Analytic and simulation techniques for the performance analysis of computer architecture, operating systems and communication networks. Rigorous development of queuing models. Study of simulation languages and models. Prerequisite: CS 450. 3-0-3
» Sample Syllabus

CS 556 Cyber-Physical Systems: Languages and Systems

Different from general-purpose and traditional computer applications, cyber-physical systems have both continuous and discrete components, hence requiring new methodologies to integrate traditional continuous control theory/systems with traditional discrete software systems. The focus of this class is to discuss and understand the challenges in emerging cyber-physical systems and to explore possible solutions from the perspectives of system specification; system modeling; programming languages; system designs; and software engineering. This course will focus on languages and systems aspects of cyber physical systems. Prerequisites: CS 450 and CS 552. 3-0-3
» Sample Syllabus

CS 557 Cyber-Physical Systems: Networking and Algorithms

The goal of the course is to provide students with the necessary foundations to apply wireless sensor networking, scheduling theory, and algorithms in the field of CPS. The focus of this class is to discuss and understand the challenges in emerging Cyber-Physical systems, open distributed real-time systems and wireless sensor networks. We will study different perspectives of wireless networks, such as various MAC protocols, routing protocols, scheduling protocols, localization, clock synchronization, data aggregation and data fusion, compressive and cooperative sensing, security, fault detection and diagnosis, online program, and networked control systems. We will also study the interaction of different systems. 3-0-3

CS 558 Advanced Computer Security

This course will teach various modern topics in network and computer security. It will provide a thorough grounding in cyber-security for students who are interested in conducting research on security and networking and for students who are more broadly interested in real-world security issues and techniques. Students will undertake a semester-long research project with the goal of technical publications. Lecture topics will include, but not limited to: (1) Unwanted traffic, such as denial of service (DoS), and spam; (2) Malware, such as botnet, worm, and virus; (3) Network configuration and defense, such as firewall, access control, and intrusion detection systems; (4) Cyber physical system security, such as critical infrastructure protection (e.g., smart grid); and (5) Hot topics, such as software-defined networking (SDN), network verification, data center and enterprise network security, web security and more. Prerequisite: CS 450 or CS 455 or CS 458. 3-0-3

CS 560 Computer Science in the Classroom

Preparation and formulation of computer science courses. Detailed weekly materials organized and perfected. The goal being to develop Open Course Ware (OCW). Prerequisite: None. 3-0-3

CS 561 The Computer and Curriculum Content

Emphasis on the presentation concepts. Selecting the best mode of delivery and using the power of the web page to enhance the presentation. Prerequisite: None. 3-0-3

CS 565 Computer Assisted Instruction

Hardware and software for the effective use of the computer in an educational environment, CAI (Computer-Assisted/Aided Instruction) being one of the major areas of investigation. Prerequisites: CS 560 or CS 561. 3-0-3

CS 566 Practicum in the Application of Computers to Education

Provides supervised experience in the development of computer-based teaching units. Evaluation of different theoretical and/or technical approaches to use of computer in the classroom. Prerequisite: CS 560 or CS 561. 1-4-3
» Sample Syllabus

CS 570 Advanced Computer Architecture

Computer system design and architecture such as pipelining and instruction-level parallelism, memory-hierarchy system, interconnection networks, multiprocessors, and clusters of servers. Selected study on current experimental computer systems. Prerequisites: CS 450 and CS 470. 3-0-3
» Sample Syllabus

CS 572 Advanced Topics in Computer Architecture

Current problems in computer architecture. Prerequisite: CS 570. 3-0-3

CS 580 Topics in Machine Learning

This course covers advanced topics in machine learning. The exact course contents may change based on recent advances in the area and the instructor teaching it. Possible topics include active learning, reinforcement learning, online learning, non-parametric learning, inductive learning, statistical relational learning, dimensionality reduction, ensemble methods, transfer learning, outlier detection, specific application areas of machine learning, and other relevant and/or emerging topics. 3-0-3. (This course replaces CS 580: Medical Informatics.)

CS 581 Topics in Artificial Intelligence

Covers various advanced topics in AI, including both theory and practice. Content may vary by instructor. Possible topics include: Planning: STRIPs planning; Partial-order planning; Situation calculus; Theorem proving; GraphPlan/SatPlan; Transformational planning; Simulated annealing; Motion planning; Case-based reasoning; Multi-agent coordination; Negotiation planning; Representation and Reasoning: Logical representation; Frame problem; Probabilistic reasoning; Bayesian networks; Game Playing: Minimax search; Evaluation functions; Learning evaluation functions; Markov Decision Processes; Reinforcement learning for games; Developing AI agents; Multi-agent planning. Prerequisite: CS 480. 3-0-3
» Sample Syllabus

CS 582 Computational Robotics

Covers basic algorithms and techniques used in Computational Robotics, to give the student a good basis for work in this highly relevant field. Topics include: Locomotion, Non-visual sensors and algorithms, Uncertainty modeling, data fusion, State space models, Kalman filtering, Visual sensor, Sampling theory, Image features, Depth reconstruction, Multiple view geometry, Ego-motion, Active vision, Reasoning, Spatial decomposition, Geometric representations, Topological representations, Path planning, Spatial uncertainty, Active control, Pose maintenance, Dead reckoning, Correlation-based localization, Sensorial maps, Task planning and task interference, Multi-agent coordination. Prerequisite: CS 430. 3-0-3
» Sample Syllabus

CS 583 Probabilistic Graphical Models

This course will cover probabilistic graphical models -- powerful and interpretable models for reasoning under uncertainty. The generic families of models such as directed, undirected, and factor graphs as well as specific representations such as hidden Markov models and conditional random fields will be discussed. The discussions will include both the theoretical aspects of representation, learning, and inference, and their applications in many interesting fields such as computer vision, natural language processing, computational biology, and medical diagnosis. CS480 and knowledge of probability and statistics are recommended. 3-0-3
» Sample Syllabus

CS 584 Machine Learning

Introduce fundamental problems in machine learning. Provide understanding of techniques, mathematical concepts, and algorithms used in machine learning. Provide understanding of the limitations of various machine learning algorithms and the way to evaluate performance of learning algorithms. Topics include: Introduction, Regression, Kernel methods, Generative learning, Discriminative learning, Neural networks, Support vector machines, Graphical models, Unsupervised learning, Dimensionality reduction. Prerequisite: CS 430. 3-0-3
» Sample Syllabus

CS 585 Natural Language Processing

An introduction to the problems of computing with human languages. Parsing. Semantic representations. Text generation. Lexicography. Discourse. Sublanguage studies. Applications to CAI, database interfaces and information retrieval. Prerequisite: CS 445. 3-0-3
» Sample Syllabus

CS 586 Software Systems Architectures

This course covers the state-of-the-art in architectural design of complex software systems. The course considers commonly-used software system architectures, techniques for designing and implementing these architectures, models and notations for characterizing and reasoning about architectures, and case studies of actual software system architectures. Prerequisite: CS 487. 3-0-3
» Sample Syllabus

CS 587 Software Project Management

Concepts of software product and process quality. Role of TQM in software project management. Use of metrics, feasibility studies, cost and effort estimates. Discussion of project planning and scheduling. The project team and leadership issues. The Capability Maturity Model: basic tenets and application of process evaluation. Prerequisite: CS 487. 3-0-3
» Sample Syllabus

CS 588 Advanced Software Engineering Development

Software development process improvement is a major objective of this course. This is achieved through a series of individual programming and process projects. Students learn to plan their projects, apply measurements, estimate size, schedule tasks, and classify defects in order to improve the quality of both their development process and their software products. Prerequisite: CS 487. 3-0-3
» Sample Syllabus

CS 589 Software Testing and Analysis

Concepts and techniques for testing and analysis of software. Software testing at the unit, subsystem, and system levels. Specification-based testing. Code-based testing. Model-based testing. Methods for test generation and validation. Static and dynamic analysis. Formal methods and verification. Reliability analysis. Prerequisite: CS 487. 3-0-3
» Sample Syllabus

CS 590 Seminar in Computer Science

Investigation and discussion by faculty and students concentrated on some topic of current interest. May be taken more than once. Prerequisite: Written instructor consent. 3-0-3

CS 591 Research and Thesis for M.S. Degree

Credit: Variable

CS 594 Research Problems

Credit: Variable

CS 595 Topics in Computer Science

This course will treat a specific topic, varying from semester to semester, in which there is a particular student or staff interest. May be taken more than once. Credit: Variable.

CS 597 Reading and Special Problems

May be taken more than once. Prerequisite: Written instructor consent. Credit: Variable

CS 612 Topics in Computer Vision

Covers advanced topics in computer vision to enhance knowledge of students interested in this highly important area. The topics in this course may change between semesters depending on the instructor teaching the course and the current state of the art in this area. Possible topics include: Image based modeling and rendering, Multiple view geometry, Auto-calibration, Object recognition, Motion analysis, Tracking, Perceptual user interfaces, Face and gesture recognition, Active vision. Prerequisite: CS 512. 3-0-3

CS 630 Advanced Topics in Algorithms

Theoretical analysis of various types of algorithms. Topics vary, and may include approximation, quantum, on-line, distributed, randomized, and parallel algorithms. Prerequisite: CS 430 and instructor consent. 3-0-3

CS 642 Advanced Topics in Networking

Introduction to advanced networking research. A particular focus area will be considered, keeping current with advances in computer networking. Quantitative methods will be emphasized. Prerequisite: CS 542. 3-0-3

CS 681 Topics in Computational Linguistics

Covers various topics in linguistics as they may be applied to various computational problems in AI, NLP, or IR. The topics in this course may change between semesters depending on the instructor teaching the course and the current state of the art in this area. Possible topics include: Systemic Functional Linguistics, Clausal structure, Group structure, Complex structure, Cognitive Linguistics, Process semantics. Prerequisite: CS 585. 3-0-3

CS 689 Advanced Topics in Software Engineering

Course content is variable and reflects the current trends in software engineering. Prerequisite: Instructor consent. 3-0-3

CS 691 Research and Thesis for Ph.D. Degree

Credit: Variable

CS 695 Doctoral Seminar

Doctoral seminar. 1-0-1

CS 750 Computer Aided Software Engineering

This course presents the state-of-the-art of computer-aided software engineering technologies. CASE encompasses a collection of automated tools and methods that provide automated support to the software specification, design, development,testing, maintenance, and management of large and complex software systems. Students will develop working understanding of CASE methodologies and tools. Prerequisite: CS 487. 2-0-2
» Sample Syllabus

CS 763 Automated Software Testing

This course will examine both the state-of-the-art and the state-of-practice in automated software testing on a system level and an unit level. Relevant issues include theoretical foundations of automated testing, automation tools and techniques, empirical studies and industrial experience. Key topics include, but are not limited to: Fundamentals of automated software testing, automated test design, modeling and generation, automated test execution, automated test management, automated test metrics, automated tools, automated feature and regression testing Environments to support cost-effective automated software testing, discussions on the barriers to industrial use of automated testing. Prerequisite: CS 487. 2-0-2
» Sample Syllabus

CSP 527 Client-Server Applications Development

Through hands-on experience in developing a client-server database project and developing and managing a client-server Internet project, this course teaches advanced skills for effective design and implementation of client-server applications. Students will examine the architectural and functionality decisions, technologies, configurations, languages, and techniques associated with client-server systems. Active/passive client-server technologies, as well as public, enterprise-wide, and inter-enterprise approaches to decision and operation support are discussed and implemented. Prerequisite: CS 425. 3-0-3
» Sample Syllabus

CSP 541 Internet Technologies

This course focuses on the technologies and protocols used by Internet WAN’s and LAN’s. The fundamental architecture, organization, and routing principles of the Internet are described. Part of the course will focus on emerging Internet technologies. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CSP 542 Internet Design and Analysis

This course examines the principles of network design. The design process is studied from requirements gathering to deployment. The student will gain experience in estimating application load, network sizing, component choice, and protocol choice. Internetworking between popular components and protocols will be studied. Analytical and simulation techniques are described and used to design several local and wide-area networks. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CSP 543 Multimedia Networking

This course covers the architectures, protocols, and design issues for multimedia networks. Topics covered include coding, compression, streaming, synchronization, QoS, and adaptation. Current tools for multimedia networking will be surveyed. Issues with multimedia application development will be explored. Students will design and develop multimedia applications. Prerequisites: CS 455 and experience programming in high-level languages. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CSP 544 System and Network Security

This course will present an in-depth examination of topics in data and network security, such as: Access control, authentication, security assessment, network and data security tools, and security policies. A significant hands-on component includes network incidents to detect and fix. Prerequisites: CS 430 and CS 455. 3-0-3
» Sample Syllabus

CSP 545 Wireless Networking Technologies and Applications

This course will present the foundation of wireless technologies and examine state-of-the-art wireless systems, services, network technologies, and security. Prerequisite: CS 542. 3-0-3
» Sample Syllabus

CSP 550 Internet Programming

This course discusses current fundamental concepts and development techniques for distributed applications. Topics covered include multithreaded programs, sockets, message-passing systems, remote method invocation and procedure calls, peer-to-peer networks, and underlying technologies for internet applications. Prerequisite: CS 455. 3-0-3
» Sample Syllabus

CSP 551 Advanced UNIX Programming

This course provides students a hands-on introduction to UNIX programming topics such as standard application programmer interfaces, concurrent programming, UNIX processes and threads, shell programming, UNIX interprocess communications, client-server designs, and application portability. Prerequisite: CS 450. 3-0-3
» Sample Syllabus

CSP 570 Data Science Seminar

This required seminar course surveys current applications of data science, bringing in lecturers from industry and academia to discuss real-world problems and how they are addressed within a data analytic framework. Students are required to attend all lectures and to give a short presentation or paper on one of the topics at the end of the semester. Co-listed as MATH 570. 1-0-1

CSP 571 Data Preparation and Analysis

This course surveys industrial and scientific applications of data analytics, with case studies, including exploration of ethical issues. Students will learn how to prepare data for analysis, perform exploratory data analysis, and develop meaningful data visualizations. They will work with a variety of real world data sets and learn how to prepare data sets for analysis by cleaning and reformatting. Students will also learn to apply a variety of different data exploration techniques including summary statistics and visualization methods. Prerequisites: CS 425 or equivalent, MATH 474 or equivalent. Co-listed as MATH 571. 3-0-3

CSP 572 Data Science Practicum

In this project-oriented course, students will work in small groups to solve real-world data analysis problems and communicate their results. Innovation and clarity of presentation will be key elements of evaluation. Students will have an option to do this as an independent data analytics internship with an industry partner. Prerequisites: COM 5xx, CS 587, either CS 584 or MATH 569, and CSP/MATH 571. Co-listed as MATH 572. 6-0-6

CSP 581 APPLIED ARTIFICIAL INTELLIGENCE PROGRAMMING

To learn AI programming algorithms and techniques in Common Lisp. Time is split between Common Lisp topics and discussions of implementation strategies for AI algorithms. Prerequisite: CS 440. 3-0-3
» Sample Syllabus

CSP 585 OBJECT-ORIENTED DESIGN PATTERNS

This course introduces the principles of design patterns for Object-Oriented software systems. A catalog of design patterns is shown, to illustrate the roles of patterns in designing and contracting complex software systems. The catalog of design patterns also provides a pragmatic reference to a well-engineered set of existing patterns currently in use. Also discussed is the impact of post-object-oriented software development on design patterns. Prerequisite: CS 445. 3-0-3
» Sample Syllabus

CSP 586 SOFTWARE MODELING AND DEVELOPMENT WITH UML

Students will obtain a significant exposure to the UML technology. This will include exposure to modeling, model-driven development, executable models, and round-trip engineering. These technologies will be explained at the application level. Prerequisite: CS 487 or CS 445. 3-0-3
» Sample Syllabus

CSP 587 Software Quality Management

Students will learn methods of software quality management. This will include exposure to software quality assurance, quality measures, and quality control. These quality management methods will be explained at the applications level. Prerequisite: CS 487. 3-0-3
» Sample Syllabus

CSP 595 Topics in Computer Science Professional Master

This course will treat a specific topic, varying from semester to semester, in which there is a particular student or staff interest. May be taken more than once.

This Computer Science course bulletin is not in final form and is subject to change without notice. Please contact the Office of the Registrar to confirm course schedules and for additional course information.