Computer Science program

CS 220 Software Design II This is a second course in the design of programs. Emphasis is placed on data abstraction and its application in design. Definitions of abstract data types are examined. The following structures are examined as methods for implementing data abstractions: recursion, generics, stacks, queues, strings, and various linked lists. Students will be expected to write several programs using these techniques in a modern programming language. Prerequisite: CS 120; concurrent enrollment in CS 225 recommended. Offered Fall, Spring.

CS 272 Digital Circuit Design for Microcontrollers I An introduction to digital circuit design in the context of embedded microcontroller devices. This will include flip-flops, sequential and combinational logic units (e.g. shift registers, half-adders, encoders * decoders, multiplexers), state machines, analog to digital and digital to analog conversion. Prerequisite: CS 225; MTH 207. Offered Annually.

CS 353 Analysis of Algorithm Complexity An in-depth analysis of the computational complexity of a wide range of algorithms for problems of fundamental importance to computer science. Algorithms to be examined include: sorting, pattern matching and various graph algorithms. Prerequisite: CS 340; MTH 207. Offered Fall - Even Numbered Years.

CS 370 Computer Architecture A presentation of the logical organization of modern digital computers. Topics include performance evaluation, instruction set design, computer arithmetic, processor control, pipelining, cache memory, memory hierarchy, memory and system buses, and I/O organization. Prerequisite: CS 270. Offered Fall, Spring.

CS 402 Web Application Development This course will give a detailed description of the core concepts and general principles of web application development. The course will cover various protocols, programming languages, scripting languages, data storage and security, layered software architectures, and graphical interface design as they relate to web development. Students will apply these techniques to the development of medium scale web application. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 202; CS 340; junior standing. Offered Spring.

CS 418 Mobile Application Development An introduction to the concepts and techniques of application development for mobile devices. The course will examine the design constraints of mobile devices, how mobile applications can leverage external data resources, integration of sensor data and the development environments of the chosen platform (e.g. iOS, Android and others). This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Repeatable for credit with different topic - maximum six. Prerequisite: CS 340; junior standing. Offered Occasionally.

CS 421 Programming Language Concepts A comparative study of the concepts underlying the design of contemporary high-level programming languages, including imperative, functional, logic and object-oriented paradigms; formal representation of syntax and semantics; control structures; data and procedural abstraction; scope and extent; parallelism and exception handling. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; CS 225 or MTH 225; junior standing. Offered Fall, Spring.

CS 431 Introduction to Robotics This course is a hands-on introduction to the algorithms and techniques required to write robot control software. Topics include the components of mobile robots and robot manipulators, manipulator kinematics, robot task planning, sensing, sensor fusion, visual servoing and robot control concepts. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; junior standing. Offered Spring - Odd Numbered Years.

CS 449 Advances in Software Engineering Introduces advanced topics in software engineering. Topics include prototyping models, risk analysis, component-oriented software development, software architectures, software reuse, software metrics and quality analysis. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 341; junior standing. Offered Fall - Even Numbered Years.

CS 451 User Interface Design This course focuses on the design and implementation of user interfaces. The topics include characteristics of user interfaces, user profiles, user interface design principles, methods and tools for user interface development, evolution of user interfaces, evaluation of user interfaces, and case studies. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; junior standing. Offered Fall - Odd Numbered Years.

CS 452 Artificial Intelligence This course is an introduction to the fundamental principles of artificial intelligence. Topics include search strategies, adversarial search, constraint satisfaction, planning and scheduling, logic and inference, accounting for uncertainty, and probabilistic reasoning. Projects include writing a substantial artificial intelligence application program. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; junior standing. Offered Fall - Odd Numbered Years.

CS 454 Digital Image Processing This course introduces the fundamentals of digital image processing techniques with an emphasis on the design and implementation of image processing algorithms. Topics include color models, point-processing techniques, convolution, Fourier domain processing, the discrete cosine transform, image compression methodologies, image restoration and enhancement, sampling and image display. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; junior standing. Offered Fall - Even Numbered Years.

CS 455 Fundamentals of Information Security This course presents the fundamental concepts of information security. Basic policies, techniques and tools for maintaining the security of host computers, information networks and computer software are presented. Topics include encryption, authentication, access control, types of attacks and mitigations, software security, network security protocols, and the concepts of trust, privacy and ethics. Students are expected to compare security policies and techniques, apply concepts using modern tools and techniques, and explore recent security events. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 270, CS 340; junior standing. Offered Spring.

CS 457 Machine Learning This course is an investigation of programs that can dynamically adapt their behavior. The course focuses on two main ideas: data classification and deciding about actions. In both cases, a learning algorithm is one that improves performance, either by generating a more accurate classifier, or by finding a choice of action that leads to better outcomes. Students will learn various computational and mathematical models and techniques that can be applied to such problems. Topics include regression algorithms, decision trees, Markov processes, neural networks, reinforcement learning algorithms, and deep learning techniques. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; junior standing. Offered Fall - Even Numbered Years.

CS 461 Introduction to Data Science This course examines key components of the data science lifecycle, including data collection and cleaning, exploratory data analysis and visualization, and extracting insight via statistical models and machine learning algorithms for regression, classification, and clustering. Algorithmic efficiency and scalability will be emphasized, and techniques for working with big data will be introduced. Students will use a modern programming language (e.g., R, Python) with appropriate packages suitable for data analysis. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; STAT 245 or CS 351; junior standing. Offered Alternate Years.

CS 464 Advanced Database Management Systems Advanced topics in database management systems. Topics include the relational data model, relational calculus, embedded SQL programming, database application programming, indexing, system software and storage structures for databases, concurrency control, crash recovery, database administration, parallel and distributed databases, object-oriented databases. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 364; junior standing. Offered Spring - Odd Numbered Years.

CS 470 Parallel and Distributed Computing A study of architectures, control software, and applications for parallel and distributed systems. A survey of parallel and distributed architectures including data flow machines, vector processors, shared memory multiprocessors, and message based multiprocessors. Software topics include process communication and synchronization, global state maintenance, negotiation, scheduling, data parallelism, control parallelism, and languages for parallel and distributed computing. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 370; junior standing. Offered Occasionally.

CS 472 Internet of Things This course explores the possibilities which are created when everyday things become connected to the internet and how this can create new ways for humans to interact with computation and for computation to enable human activities. This course involves building small, sensor equipped hardware devices and cloud based software systems using various technologies. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340, CS 372; junior standing. Offered Annually.

CS 475 Computer Graphics and Modeling An introduction to computer graphics in modern computing environments. Topics include geometric transformations, fundamental drawing algorithms, scalable vector graphics (SVG), OpenGL, WebGL, surface shaders, scene graphics, photorealistic rendering, surface mesh data structures, animation and modeling and GPGPU computing. This course is taught largely at an undergraduate level. Graduate students will have additional course requirements/expectations. Prerequisite: CS 340; MTH 207; junior standing. Offered Fall - Odd Numbered Years.

CS 499 Research in Computer Science An opportunity to become acquainted with literature in the field and to work on a professional level research project within an area of interest of the computer science faculty. A seminar reviewing the results of the study will be a requirement for completion of the course. Repeatable for credit - maximum six. Consent of instructor. Offered Fall, Spring.