Computer Science Department

Course Descriptions

Computer Applications

• CAPP 171 - Communicating via Computers

  Credits: 3. Offered intermittently. Prereq., previous computer experience or consent of instr. The use of the computer for information presentation and communication; emphasis placed on the use of electronic resources for the access, management, and presentation of information. Students taking CS classes with computer programming components should expect to use additional computer lab time outside of class.

Computer Science/Programming

• CSCI 100 - Intro to Programming

  Credits: 3. Offered autumn and spring. This course covers basic programming concepts such as variables, data types, iteration, flow of control, input/output, functions, and objects. The course will also cover programming ideas such as data structures, algorithms, modularity, and debugging. Students will learn about the role computation can play in solving problems by writing interesting programs to solve useful goals. No prior programming experience is expected. (Two hours independent lab per week.) Credit not allowed for both CSCI 100 and CSCI 110.

• CSCI 105 - Computer Fluency

  Credits: 3. Offered autumn and spring. Introduces the skills and concepts of information technology, both from practical and a more theoretical point of view. During lectures and interactive computer labs, students will explore a wide range of digital and information technologies, including common PC applications, networking, databases, privacy, and security. Credit not allowed for both CSCI 105 and CRT 111 and CS 111.

• CSCI 106 - Careers in Computer Science

  Credits: 1. Offered autumn.  Exploration of various careers available in the general area of Computer Science.  Includes discussion of strategies for success in the major.  Computer Science faculty members also will discuss possible undergraduate research opportunities and motivation for graduate education.

• CSCI 135 - Fund of Computer Science I

  Credits: 3. Offered autumn and spring. Prereq., computer programming experience in a language such as BASIC, Pascal, C, etc.; CSCI 104 highly recommended as prereq. or coreq. Fundamental computer science concepts using the high level structured programming language, Java.

• CSCI 136 - Fund of Computer Science II

  Credits: 3. Offered autumn and spring. Prereq., CSCI 135; coreq., M 115 or M 151 or consent of instr. Continuation of CSCI 135. Survey of computer science topics including recursion, algorithms, basic data structures, operating systems, artificial intelligence, graphics, user interfaces, and social and ethical implications of computing.

• CSCI 172 - Intro to Computer Modeling

  Credits: 3. Offered autumn and spring. Problem solving and data modeling using computer productivity software. Emphasis using spreadsheets and database for data analysis. Credit not allowed for CSCI 172, CRT 172, and CS 172.

• CSCI 181 - Web Design and Programming

  Credits: 3. Electronic Publishing on the World Wide Web

• CSCI 191 - Special Topics

  Credits: 0 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Experimental offerings of visiting professors, experimental offerings of new courses, or one-time offerings of current topics. Students taking CS classes with computer programming components should expect to use additional computer lab time outside of class.

• CSCI 198 - Internship

  Credits: 1 TO 6. Offered intermittently. Prereq., consent of department. Extended classroom experience which provides practical application of classroom learning during placements on and off campus. Prior approval must be obtained from the faculty supervisor and the Internship Services office. A maximum of 6 credits of Internship (198, 298, 398, 498) may count toward graduation.

  Course Attributes:

  • Internships/Practicums

• CSCI 205 - Programming Languages w/ C/C++

  Credits: 4. Offered spring.  Prereq., CSCI 232 and M 225.  Concepts and principles of programming languages with an emphasis on C, C++, and object-oriented programming.  Syntax and semantics of object-oriented languages.  Principles and implementation of late binding, memory allocation and de-allocation, type-checking, scope, polymorphism, inheritance.

• CSCI 216E - Technology, Ethics & Society

  Credits: 3. An examination of ethical issues related to new technologies in the context of ethical theory in the western secular tradition. Focus will be on applying central concepts, principles, and problems of ethical theory to particular areas of technology, such as artificial intelligence and robotics, social networks, nanotechnology, genetic engineering, and privacy in a digital age.

  Course Attributes:

  • Ethical & Human Values Course
  • Writing Course-Intermediate

• CSCI 232 - Data Structures and Algorithms

  Credits: 4. Offered autumn. Prereq., 'B-' or better in CSCI 136; or consent of instr. Abstract data types, algorithm analysis, stacks, queues, lists, recursion, trees, hashing, graphs, and applications of data structures in algorithm development. Python programming language used.

• CSCI 250 - Computer Mdlng/Science Majors

  Credits: 3. Offered autumn. Prereq., basic computer and spreadsheet literacy; coreq., M 162 or 171.  An introduction to programming in Python with an emphasis on problems arising in the sciences, including: function plotting, data fitting, file input/output, solving ordinary differential equations, matrix manipulation, and sensor networks. A student can take at most one of CSCI 172, CSCI 250, CRT 280, and CRT 281 for credit.

• CSCI 291 - Special Topics

  Credits: 1 TO 6. (R-9) Offered intermittently. Prereq., consent of instr. Experimental offerings of visiting professors, experimental offerings of new courses, or one-time offerings of current topics.

  Course Attributes:

  • Writing Course-Lower-Division

• CSCI 298 - Internship

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of department. Extended classroom experience which provides practical application of classroom learning during placements on and off campus. Prior approval must be obtained from the faculty supervisor and the Internship Services office. A maximum of 6 credits of Internship (198, 298, 398, 498) may count toward graduation.

  Course Attributes:

  • Internships/Practicums

• CSCI 315E - Computers, Ethics, and Society

  Credits: 3. Offered autumn. Prereq., University approved intermediate level writing course. Ethical problems that computer scientists face. The codes of ethics of professional computing societies. The social implications of computers, computing, and other digital technologies.

  Course Attributes:

  • Ethical & Human Values Course
  • Writing Course-Advanced

• CSCI 323 - Software Science

  Credits: 3. Offered autumn. Prereq., CSCI 136. Study, implementation, and assessment of software processes, techniques, methods, and CASE tools.  Project management and cost estimation techniques will be examined.  A group project may be required.

• CSCI 332 - Design/Analysis of Algorithms

  Credits: 3. Offered spring. Prereq., CSCI 232 and M 225 or consent of instr. Algorithm design, analysis, and correctness. Commonly used algorithms including searching and sorting, string search, dynamic programming, branch and bound, graph algorithms, and parallel algorithms. Introduction to NP-complete problems.

• CSCI 340 - Database Design

  Credits: 3. Offered spring.  Prereq., CSCI 232 or consent of instr.  Fundamentals of data modeling, the relational mode, normal forms, file organization, index structures and SQL.  Major project involving the design and implementation of a relational database.

• CSCI 361 - Computer Architecture

  Credits: 3. Offered spring.  Prereq., CSCI 136 or consent of instr.  Functional view of computer system components, BCPU, ALU, memory, bus, cache, I/O module.  Instruction set design: formats, addressing modes.  Basic circuit design.  Pipelining and assembly language.  Interrupt handling.  Implementation of ALU and control unit.  Detailed design of an RISC-like instruction set.  Datapath and performance comparisons.  Basic multiprocessor design.

• CSCI 390 - Research

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Directed individual research and study appropriate to the back ground and objectives of the student.

  Course Attributes:

  • Research & Creative Schlrshp

• CSCI 391 - Special Topics

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., junior standing. Experimental offerings of visiting professors, experimental offerings of new courses, or one-time offerings of current topics.

• CSCI 394 - Seminar

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Guidance in special work.

• CSCI 398 - Internship

  Credits: 1 TO 3. (R-3) Offered intermittently. Prereq., consent of department. Business or government internship. Prior approval must be obtained from faculty supervisor and the Internship Services office. Only three credits applicable to computer science major or minor. A maximum of 6 credits of Internship (198, 298, 398, 498) may count toward graduation.

  Course Attributes:

  • Internships/Practicums

• CSCI 411 - Advanced Web Programming

  Credits: 3. Offered intermittently. Prereq., CSCI 136.  Programming and software development techniques for developing web-based applications.  Scripting and other programming languages that are used for web-based development.

• CSCI 412 - Game and Mobile App

  Credits: 3. Offered intermittently. Prereq., CSCI 232 and 323. Programming and software development techniques for developing gaming and mobile applications. Multiple gaming environments and mobile programming languages are introduced and examined to build modern applications.

• CSCI 426 - Adv Prgrmng Theory/Practice I

  Credits: 3. Offered autumn. Prereq., CSCI 205, 232, 323 and M 225, or consent of instr. Examination and implementation of modern best practices in the areas of software design, coding, testing and maintenance. Focus on design patterns and design pattern languages used to build modern software systems in a variety of areas.

• CSCI 427 - Adv Prgrmng Theory/Practice II

  Credits: 3. Offered spring. Prereq., CSCI 426. Design and implementation of a major software project in a group setting, with required documentation, presentation, installation, and approval by the instructor.

• CSCI 438 - Theory of Computation

  Credits: 3. Offered intermittently. Prereq., M 225 or M 307. This course focuses on understanding the limitations & capabilities of abstract models of computation, through rigorous mathematical analysis. Topics will include finite & pushdown automata, nondeterministic computation, regular expressions, generative grammars, Turing machines, undecidability, and computational complexity.

• CSCI 441 - Computer Graphics Programming

  Credits: 3. Offered intermittently. Prereq., CSCI 232 and M 221 or consent of instr. The graphics pipeline, its implementation in hardware and emphasis on the programmable portions of the pipeline. Matrix transformations for modeling, viewing, clipping, and windowing. Application of lighting, coloring, and texturing models. Hierarchical modeling of objects. Programmable shaders. OpenGL and WebGL.

• CSCI 443 - User Interface Design

  Credits: 3. Offered intermittently. Prereq., CSCI 232 or consent of instr. Introduction to usability and key concepts of human behavior. Focus on the process of user-centered design, including requirements specification, prototyping, and methods of evaluation. Incorporation of regular design critiques of classmates' work, and emphasis on both oral and written communication skills. Credit not allowed for CSCI 543 and this course.

  Course Attributes:

  • Co-Convened Course

• CSCI 444 - Data Visualization

  Credits: 3. Offered intermittently. Prereq., M 171; programming experience; and junior, senior, or graduate status; or consent of instr. Visualization fundamentals and applications using special visualization software; formulation of 3-D empirical models; translation of 3-D models into graphical displays; time sequences and pseudo-animation; interactive versus presentation techniques; special techniques for video, CD and other media.

• CSCI 446 - Artificial Intelligence

  Credits: 3. Offered intermittently. Prereq., M 225 or M 307, and CSCI 232, or consent of instr. Using computers and software to solve problems that require intelligence. Specific topics may include knowledge representation, logical and probabilistic reasoning, machine learning, planning, game playing, information retrieval, computer vision, and robotics.

• CSCI 447 - Machine Learning

  Credits: 3. Offered intermittently.  Prereq., CSCI 232 or consent of instr.  Introduction to the framework of learning from examples, various learning algorithms such as neural networks, and generic learning principles such as inductive bias, Occam's Razor, and data mining.  Credit not allowed for both CSCI 447 and CSCI 547.

  Course Attributes:

  • Co-Convened Course

• CSCI 448 - Pattern Recognition

  Credits: 3. Offered intermittently. Prereq., Junior or Senior status. Introduction to the framework of unsupervised learning techniques such as clustering (agglomerative, fuzzy, graph theory based, etc.), multivariate analysis approaches (PCA, MDS, LDA, etc.), image analysis (edge detection, etc.), as well as feature selection and generation. Emphasis will be on the underlying algorithms and their implementation. Credit not allowed for both CSCI 448 and CSCI 548.

  Course Attributes:

  • Co-Convened Course

• CSCI 451 - Computational Biology

  Credits: 3. Offered Autumn.  Designed for attendance by both computer scientists and biologists.  The course will explore the importance of interdisciplinary partnerships between these two fields.  Students will learn to use various existing computational tools for investigating genomic and other biological data.  This will include tools for performing sequence alignments and searches, building phylogenetic trees, predicting RNA secondary structure, and predicting protein tertiary structure.  The underlying algorithmic approaches taken by these tools will be discussed, and in some cases, actually implemented by the class participants.  The course will examine the data repositories where genomic and other biological data are stored.  There will be some light programming required using PERL as the language of choice.  It is assumed that the class participants have no experience programming in PERL and will learn this skill as part of the course. Credit not allowed for CSCI 558 and this course.

  Course Attributes:

  • Co-Convened Course

• CSCI 460 - Operating Systems

  Credits: 3. Offered autumn. Prereq., CSCI 232, or consent of instr. Operating system design principles. Processes, threads, synchronization, deadlock, memory management, file management and file systems, protection, and security, comparison of commonly used existing operating systems, writing programs that make use of operating system services. It is recommended, but not required, that the student also attend Programming Languages (in order to be prepared to write C programs) and Architecture (in order to understand interactions between the operating system and processor hardware) prior to attending this course.

• CSCI 464 - Applications of Mining Big Data

  Credits: 3. Offered intermittently. Prereq., upper division or consent of instr. Co-convenes with CSCI 564. Introduction to existing data mining software systems and their use, with focus on practical exercises. Topics include data acquisition, data cleansing, feature selection, and data analysis. Credit not allowed for both CSCI 464 and CSCI 564.

  Course Attributes:

  • Co-Convened Course

• CSCI 466 - Networks

  Credits: 3. Offered spring. Prereq., CSCI 232. Concepts and practice of computer networking, network protocol layers, switching, routing, flow, and congestion control.  Network programming.

• CSCI 477 - Simulation

  Credits: 3. Co-convene with CSCI 577. Prereq., M 172, CSCI 135, or consent of instr. Matrix languages. ODE solving; Euler-Richardson, Runge-Kutta, PDE solving; finite differences, finite elements, multi-grid techniques. Discrete methods for solution, renormalization group method, critical phenomena. Emphasis on presentation of results and interactive programs. Credit not allowed for CSCI 577 and this course.

  Course Attributes:

  • Co-Convened Course

• CSCI 480 - Applied Parallel Computing Techniques

  Credits: 3. Prereq., CSCI 205 and 232, or instructor consent. This course is an introduction to parallelism and parallel programming. Topics include the various forms of parallelism on modern computer hardware (e.g. SIMD vector instructions, GPUs, multiple cores, and networked clusters), with coverage of locality and latency, shared vs non-shared memory, and synchronization mechanisms (locking, atomicity, etc). We will introduce patterns that appear in essentially all programs that need to run fast. We will discuss how to recognize these patterns in a variety of practical problems, discuss efficient algorithms for implementing them, and how to compose these patterns into larger applications. We will address computer architecture at a high level, sufficient to understand the relative costs of operations like arithmetic and data transfer. We also introduce useful tools for debugging correctness and performance of parallel programs. Assignments will include significant parallel programming projects. Co-convenes with CSCI 580. Credit not allowed for both CSCI 480 and CSCI 580.

  Course Attributes:

  • Co-Convened Course

• CSCI 490 - Research

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Directed individual research and study appropriate to the back ground and objectives of the student.

  Course Attributes:

  • Research & Creative Schlrshp

• CSCI 491 - Special Topics

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Experimental offerings of visiting professors, experimental offerings of new courses, or one-time offerings of current topics.

• CSCI 492 - Independent Study

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Course material appropriate to the needs and objectives of the individual student.

• CSCI 494 - Seminar

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Guidance in special work.

• CSCI 498 - Internship

  Credits: 1 TO 3. (R-3) Offered Intermittently. Prereq., consent of department. Business or government internship. Prior approval must be obtained from the faculty supervisor and the Internship Services office. Only three credits of CSCI 398 and/or CSCI 498 applicable to computer science major or minor. A maximum of 6 credits of Internship (198, 298, 398, 498) may count toward graduation.

  Course Attributes:

  • Internships/Practicums

• CSCI 499 - Senior Thesis/Capstone

  Credits: 1 TO 6. (R-6) Offered every term.  Prereq., consent of thesis/project director and chair of the Computer Science Department.  Senior thesis for computer science majors and/or Watkins scholars.

• CSCI 521 - IT Infrastructure

  Credits: 3. Offered infrequently.  Prereq., CSCI 446 or IS 372 or consent of instr. Identification and classification of background environment, hardware, software, and service components in an enterprise IT environment; management and security concerns for each component; consideration of how the components fit together to form an enterprise information technology environment. Level: Graduate

• CSCI 531 - Desgn & Anal Algorithms

  Credits: 3. Offered intermittently. Prereq., CSCI 332. Algorithm design, analysis, and correctness, with an emphasis on more advanced techniques than covered in CS 332. Design of algorithms by induction. Recurrences and their solutions. Parallel algorithms. Complexity theory: NP-hard and NP-complete problems. Approximation algorithms for intractable problems. Level: Graduate

• CSCI 543 - Human-Computer Interaction

  Credits: 3. Offered intermittently. Prereq., CSCI 232 or consent of instr. Principles of good design for interactive systems and web-based applications. User-centered design methodology including requirements specification, low and high-fidelity prototyping, heuristic evaluation, cognitive walkthrough, predictive modeling, and usability testing. Advanced HCI research project. Credit not allowed for both CSCI 443 and CSCI 543. Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 547 - Machine Learning

  Credits: 3. Offered intermittently. Prereq., CSCI 232 or consent of instr. Fundamentals of machine learning including neural networks, decision trees, Bayesian learning, instance-based learning, and genetic algorithms; inductive bias, Occam's razor, and learning theory; data mining; software agents. Credit not allowed for CSCI 447 and CSCI 547. Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 548 - Pattern Recognition

  Credits: 3. Offered intermittently.  Introduction to the framework of unsupervised learning techniques such as clustering (agglomerative, fuzzy, graph theory based, etc.), multivariate analysis approaches (PCA, MDS, LDA, etc.), image analysis (edge detection, etc.), as well as feature selection and generation. Techniques in exploratory data analysis when faced with large, multivariate datasets. Opportunities at implementation of some algorithmic approaches as well as use of preexisting tools such as the R-project statistics package. Emphasis will be on the underlying algorithms and their implementation. Credit not allowed for both CSCI 448 and CSCI 548. Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 555 - Topics Artificial Intelligence

  Credits: 3. Offered intermittently. Prereq., M 225 or M 307, and CSCI 232, or consent of instr. The study and design of artificial intelligent agents. Specific topics may include knowledge representation, logical and probabilistic reasoning, machine learning, planning, game playing, information retrieval, computer vision, and robotics. Level: Graduate

• CSCI 558 - Intro to Bioinformatics

  Credits: 3. Offered autumn.  Prereq., consent of instr.  Introduction and use of biological data sources available in the post human genome project era.  Topics include basic algorithms for alignment of genome sequences and prediction of protein structures, as well as more advanced representational and algorithmic issues in protein structure, genome sequence computation, and systems biology.  Discussion of state of the art bioinformatics projects that are being developed between the Department of Computer Science and the School of Pharmacy.  Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 564 - Applications of Mining Big Data

  Credits: 3. Offered intermittently. Co-convenes with CSCI 464. Introduction to existing data mining software systems and their use, with focus on practical exercises. Topics include data acquisition, data cleansing, feature selection, and data analysis. Credit not allowed for both CSCI 464 and CSCI 564. Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 565 - Database Systems

  Credits: 3. Offered intermittently. Prereq., CSCI 205 and 340, or consent of instr. Relational database theory, data models, query languages, transaction processing, security, and concurrency. Level: Graduate

• CSCI 577 - Simulation Modeling

  Credits: 3. Co-convene with CSCI 477.  Prereq., M 172, CSCI 135, or consent of instr. Matrix languages. ODE solving; Euler-Richardson, Runge-Kutta, PDE solving; finite differences, finite elements, multi-grid techniques. Discrete methods for solution, renormalization group method, critical phenomena. Emphasis on presentation of results and interactive programs. Conduct, document, and present graduate level research involving computer simulation methods. Credit not allowed for CSCI 477 and this course. Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 580 - Applied Parallel Computing Techniques

  Credits: 3. Offered intermittently. Prereq., CSCI 232, 205. Parallel processing architectures and programming languages. Co-convenes with CSCI 580. Credit not allowed for both CSCI 480 and CSCI 580. Level: Graduate

  Course Attributes:

  • Co-Convened Course

• CSCI 594 - Graduate Seminar

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Seminar on current research topics in computer science. Level: Graduate

• CSCI 595 - Special Topics

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Experimental offerings of visiting professors, experimental offerings of new courses, or one-time offering of current topics. Level: Graduate

  Course Attributes:

  • Internships/Practicums

• CSCI 596 - Independent Study

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Course material appropriate to the needs and objectives of the individual student. Level: Graduate

  Course Attributes:

  • Service Learning/Volunteer

• CSCI 597 - Research

  Credits: 1 TO 6. (R-6) Offered intermittently. Prereq., consent of instr. Directed individual research and study appropriate to the back ground and objectives of the student. Level: Graduate

• CSCI 598 - Internship

  Credits: 1 TO 9. (R-3) Offered intermittently. Prereq., consent of department. Business or government internship. Prior approval must be obtained from faculty supervisor and the Internship Services office. Only three credits applicable to computer science major or minor. Level: Graduate

  Course Attributes:

  • Internships/Practicums

• CSCI 599 - Thesis/Project

  Credits: 1 TO 6. (R-6) Offered every term. Prereq., consent of instr. Research for and preparation of the master thesis or professional paper. Level: Graduate