2024-2025 Course List

The first in a two-semester sequence of capstone design. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Course must be taken concurrently with CS 495.

Prerequisites:

CS 301, CS 302, CS 303, CS 304, CS 392W

The first in a two-semester sequence of capstone design. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Course must be taken concurrently with CS 495.

Prerequisites:

CS 301, CS 302, CS 303, CS 304, CS 392

The second in a two-semester sequence of capstone design and the fourth project class overall. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Expectations include public presentation of project work, patent applications, and/or plan for commercialization of project. Course must be taken concurrently with CS 495.

Prerequisites:

CS 491W and (CS 306, CS 401, CS 403, CS 406, CS 410, CS 420, CS 435, CS 440, CS 445, CS 450, CS 465, CS 470, CS 480, or CS 485)

The second in a two-semester sequence of capstone design and the fourth project class overall. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Expectations include public presentation of project work, patent applications, and/or plan for commercialization of project. Course must be taken concurrently with CS 495.

Prerequisites:

CS 491 and (CS 306, CS 401, CS 403, CS 406, CS 410, CS 420, CS 435, CS 440, CS 445, CS 450, CS 465, CS 470, CS 480, or CS 485)

Workshop topics will be announced. Workshops on different topics may be taken for credit.

Prerequisites:

Consent of Instructor

Students learn about computer science practice through seminars with faculty, graduate students, undergraduate students admitted to the CS major, visiting researchers, and industry members. CS students are assisted in their development as learners and professional citizens through workshops. This course is repeated by upper-division Computer Science students every semester.

Prerequisites:

Admission to major.

Special topics not covered in other courses. May be repeated for credit on each new topic. VariablePrereq: Consent

Prerequisites:

Consent

This course is designed to provide students with an opportunity to utilize their training in a real-world environment. Participants work under the guidance and direction of a full-time staff member. (At most 4 hours towards the CS major.)Prereq: Permanent admission to the CS major, CS 300, consent

Prerequisites:

Permanent admission to the CS major, CS 300, consent.

Advanced study and research required. Topic of the senior thesis determined jointly by the student and the faculty advisor.Fall, Spring Prereq: Senior standing and consent

Prerequisites:

Senior standing and consent

Problems in the field of computer science are studied on an individual basis under the guidance of a faculty mentor.Fall, Spring Prereq: Consent

Prerequisites:

Consent

Current processes, methods, and tools related to formal methods for modeling and designing software systems. Topics include software architectures, methodologies, model representations, component-based designs, patterns, frameworks, CASE-based designs, and case studies.

This course studies the theoretical underpinnings of modern computer science, focusing on three main models of computation: DFA, PDA, and Turing Machines. Students determine model capabilities and limitations are: what is and is not computable by each of them. Pre: With permission by the instructor.

This course covers High Performance Computing (HPC) techniques used to address problems in Computational Science. Topics include the application areas and basic concepts of parallel computing, hardware design of modern HPC platforms and parallel programming models, methods of measuring and characterizing serial and parallel performance, and computational grid technologies. Pre: With permission by the instructor.

This course provides an advanced understanding of topics covered in COMS 320. The course addresses advanced topics in computer architecture including a major emphasis on measuring and improving computer performance. Topics include advances in pipelining and analysis and optimization of storage systems and networks, multiprocessor challenges and trends. Pre: With permission by the instructor.

This course provides an overview of embedded and real-time systems and their development. Students will design and build a real-time operation system with a microprocessor to host real-time service data processing using sensor/actuator devices. The course covers design principles, methodologies, design tools and problem solving techniques. Pre: With permission by the instructor.

This course offers an overview of the field of Artificial Intelligence (AI). Basic introductory concepts and a history of the field are covered. Emphasis is placed on the knowledge representation and reasoning strategies used for AI problem solving. Solutions are found using the LISP programming language. Pre: With permission by the instructor.

This course presents an overview of the field of computational linguistics. Topics include regular expressions, finite state automata, information theory, context free grammars, hidden Markov models and Viterbi algorithms. Students will work on problems within the field including parsing, machine translation, speech recognition, information extraction and parsing. Pre: With permission by the instructor.

This course offers a blended view of computer science, information science, and statistics for storing, accessing, modeling, and understanding large data sets. Topics include fundamental data mining algorithms: decision trees, classification, regression, association rules, statistical models, neural networks, and support vector machines. Pre: With permission by the instructor.

This course provides advanced coverage of data communication and networking protocols. The course introduces the principles, protocols and performance evaluation techniques of various advanced networking technologies. Topics include error detection and recovery, flow control, routing, data throughput, and performance analysis of existing and emerging Internet protocols. Pre: With permission by the instructor.

This course covers emerging mobile and wireless data networks. The course reviews significant standard wireless protocols (e.g., Bluetooth, IEEE 802.11, RFID, and WAP), and explores technologies for the development of mobile and wireless applications (e.g., J2ME, WML, Brew). Includes research, design and implementation of wireless, mobile application. Pre: With permission by instructor.

This course studies the historical and current concepts and implementations of computer operating systems. Basic operating systems topics include processes, interprocess communication, interprocess synchronization, deadlock, memory allocation, segmentation, paging, resource allocation, scheduling, file systems, storage, devices, protection, security, and privacy. Pre: With permission by the instructor.

The second of a two-course sequence on graphics and game programming. The course concentrates on 3D graphics including modeling, rendering, and animation for computer games and graphic simulations. Programs are created using a current graphics and game development environment.

This course offers an introduction to the specification and implementation of modern compilers. Topics covered include lexical scanning, parsing, type checking, code generation and translation, an introduction to optimization, and compile-time and run-time support for modern programming languages. Students will build a working compiler. Pre: With permission by the instructor.

This course covers advanced object-oriented programming for general purpose software development. Topics include tools and processes appropriate for employing object-oriented designs and programming with a significant software development environment and advanced data structures and algorithms, graphical user interfaces, and software development processes. Pre: With permission by the instructor.

Building upon the introduction provided in CS 300, provides a formal presentation of software engineering concepts. Additional topics include alternative design methods, software metrics, software project management, reuse and re-engineering.