Academic Catalog 2022-2023

Computer Science

Faculty

Nathan D. Axvig, sabbatical 2022-2023
Ahmed M. Kamel, sabbatical spring 2023
Damian J. Lampl
 

Courses

CSC 104  -  Software Applications for Business,  2 credits.  

Designed to prepare the student for Microsoft certification exams in PowerPoint, Excel, and Outlook, this course will guide the student in developing the skills necessary to be proficient in each of the software applications.

Frequency: Every Semester  
CSC 125  -  Introduction to Computer Science,  4 credits.  

An introduction to an object oriented programming language, algorithm design, structured and object-oriented programming techniques. No prior programming experience is assumed. Prerequisite: higher algebra.

Frequency: Every Semester  
Core designations: Mathematics K  
CSC 225  -  Fundamental Structures,  4 credits.  

Intermediate data structures and techniques of object-oriented and structured programming. Discrete data types and structures, including arrays, files, sets, lists, trees, hash tables, sorting and recursion. Small to medium-scale programs are developed.

Frequency: Every Semester  
Prerequisites: CSC 125  
CSC 250  -  Pre-May Seminar,  4 credits.  
Frequency: Not offered on a Regular Basis  
CSC 300  -  May Seminar,  4 credits.  
Frequency: May Seminar  
Core designations: International-Global Prspct G  
CSC 310  -  Web Design and Programming,  3 credits.  

Basics of programming echniques for the World Wide Web. Provides an introduction to several web design methodologies including methodologies for data access and presentation.

Frequency: Every Year - First Semester  
Prerequisites: CSC 125  
This course is PEAK Optional  
CSC 311  -  Mobile Applications Development,  3 credits.  

Basics of software development for mobile devices. Provides an introcution to programming techniques for mobile devices including mobile web access and mobile access to databases.

Frequency: Alternate Years - 2nd Semester  
Prerequisites: CSC 225  
This course is PEAK Optional  
CSC 330  -  Introduction to Database Management,  3 credits.  

An introduction to database theory and practice. Topics include relational database design, ER modeling, normalization, SQL/embedded SQL, concurrency control, data warehousing and other emerging database technologies. Practical software engineering principles are emphasized through student projects.

Frequency: Every Year - First Semester  
Prerequisites: CSC 125  
CSC 335 / BUSN 460 / MATH 335  -  Operations Management/Research,  4 credits.  

An introduction to the theory and practice of quantitative modeling and optimization, with applications to computer simulation and business resource management. Possible topics include linear and nonlinear programming, network analysis, game theory, deterministic and probabilistic models. Prerequisite: consent of the instructor.

Frequency: Every Year - First Semester  
Corequisites: PEAK 400  
Core designations: Mathematics K  
This course is PEAK Required  
CSC 340  -  Principles of Software Engineering,  3 credits.  

An overview of the systems development process. Includes: tools/techniques for describing processes, data flows, data structures, file designs, input/output designs, program specifications and prototyping for systems. Discovery, problem-solving and communications skills as employed by the systems analyst are also covered.

Frequency: Alternate Years - 1st Semester  
Prerequisites: CSC 225  
CSC 345  -  Computer Networks,  3 credits.  

This course is introduction to the fundamental concepts in the design and implementation of computer networks. Topics include network topologies, OSI and TCP/IP reference models, local area networks, Wi-Fi, routing. Examples and projects will focus primarily on TCP/IP protocols.

Frequency: Alternate Years - 1st Semester  
Prerequisites: CSC 225  
CSC 380  -  Special Topics,  0-4 credits.  

An opportunity to study in depth an advanced topic of current interest. Students work as teams to complete several extended research projects.

Frequency: Not offered on a Regular Basis  
Repeatable: Yes  
CSC 390  -  Cooperative Education,  1-8 credits.  
Frequency: Every Semester  
This course is PEAK Optional  
Repeatable: Yes  
CSC 410  -  Artificial Intelligence,  3 credits.  

This course is intended to give a wide exposure to the history and current state of the field of Artificial Intelligence. Students will be introduced to the different Artificial Intelligence methodologies and familiarized with the relative strenghts and weaknesses of these technologies.

Frequency: Alternate Years - 1st Semester  
Prerequisites: CSC 330  
CSC 420  -  Operating Systems,  3 credits.  

A study of how computers manage their resources. Highlights include concurrency, memory management, process and processor management and scheduling, device control, performance evaluation and system security. Several operating systems are compared.

Frequency: Alternate Years - 1st Semester  
Prerequisites: CSC 225  
CSC 430  -  Principles of Programming Languages,  3 credits.  

An introduction to principles of programming language design. Topics include regular and context-free grammars, parsing, static and dynamic scoping, and type checking. Students will explore the dimensions of computer languages drawn from several different programming paradigms.

Frequency: Every Year - First Semester  
Prerequisites: CSC 225  
CSC 445  -  Intro to Computer Security,  3 credits.  

Provides an introduction to a variety of topics in computer security both from a technical and from a human resource point of view.

Frequency: Alternate Years - 2nd Semester  
Prerequisites: CSC 330  
CSC 470  -  Applied Software Project,  3 credits.  

This course will allow the students to apply all their knowledge from the computer science major to implement a real world software project. Students will simultaneously learn techniques for insuring quality software and will apply these techniques among other techniques to implement a software project with direct applicability to a large problem situation.

Frequency: Alternate Years - 2nd Semester  
Prerequisites: CSC 330 and CSC 340  
This course is PEAK Optional  
CSC 480  -  Independent Study,  1-4 credits.  

This course provides an opportunity for individual students to conduct in-depth study of a particular topic under the supervision of a faculty member. Contact the department or program chair for more information.

Frequency: Not offered on a Regular Basis  
Repeatable: Yes  
CSC 483  -  Human-Computer Interaction,  3 credits.  

A study of the mechanisms for interaction (i.e. user interfaces) between users and computing equipment whether this computing equipment comes in the form of a computer or of a computing system embedded within any other system (manufacturing machinery controllers, medical equipment, aircraft, traffic lights, home appliances...etc.) Human computer interaction focuses on user satisfaction as well as ensuring user interfaces that avoid erroneous use of computing equipment that may at times have catastrophic results.

Frequency: Alternate Years - 2nd Semester  
CSC 487  -  Directed Research,  1-4 credits.  

This course provides an opportunity for individual students to conduct research in a specific area of study, completed under the direction of a faculty mentor. Specific expectations of the research experience to be determined by the faculty. Repeatable for credit. Prerequisite: consent of instructor.

Frequency: Not offered on a Regular Basis  
Repeatable: Yes  
DATA 200  -  Introduction to Data Analytics,  4 credits.  

This is an introductory course in using modern data analysis concepts and tools to gain insight and make decisions in a business or organizational setting. Topics include data storage, business intelligence, basic data mining and modeling, visualization, prediction/forecasting, and clustering/segmentation. Students will complete at least one data analytics project, starting from an original research question and concluding with actionable recommendations.

Frequency: Every Semester  
Core designations: Mathematics K  
DATA 316 / MATH 316  -  Applied Statistical Models,  4 credits.  

An introduction to the construction and analysis of least-squares models, including multiple regression, ANOVA, ANCOVA, and mixed models. Generalized linear models will also be presented, with special attention paid to logistic regression and log-linear models. Examples and applications will be drawn from various disciplines, including biology, medicine, economics, engineering, and the social sciences.

Frequency: Alternate Years - 2nd Semester  
Prerequisites: MATH 205 or MATH 315 or BUSN 320 or PSYC 230 or SOC 228 or MATH 200  
DATA 317  -  Forecasting,  4 credits.  

Forecasting is the science of predicting future events and outcomes. In this course students will learn how to effectively use both data and theory to create forecasts and how to quantify and communicate uncertainty in forecasts. Topics include random walks, Markov models, time series analysis, Bayesian methods and qualitative forecasting.

Frequency: Alternate Years - 1st Semester  
Prerequisites: DATA 200 or MATH 205 or MATH 315 or BUSN 320  
DATA 318  -  Data Mining,  4 credits.  

Data mining is the study of discovering and assessing patterns, relationships and information within large datasets. This course provides an introduction to data mining with an emphasis on predictive modeling techniques and machine learning algorithms. Examples and applications will be drawn from various disciplines.

Frequency: Alternate Years - 2nd Semester  
Prerequisites: CSC 125 and (DATA 200 or MATH 205 or MATH 315 or BUSN 320 or PSYC 230 or SOC 228)  
DATA 380  -  Special Topics,  0-4 credits.  

Courses covering various topics of interest in this particular discipline are offered regularly. Contact department or program chair for more information.

Frequency: Not offered on a Regular Basis  
Repeatable: Yes  
DATA 390  -  Cooperative Education,  1-8 credits.  
Frequency: Not offered on a Regular Basis  
This course is PEAK Optional  
Repeatable: Yes  
DATA 480  -  Independent Study,  1-4 credits.  

This course provides an opportunity for individual students to conduct in-depth study of a particular topic under the supervision of a faculty member. Contact the department or program chair for more information.

Frequency: Not offered on a Regular Basis  
Repeatable: Yes  
DATA 487  -  Directed Research,  1-4 credits.  

This course provides an opportunity for individual students to conduct research in a specific area of study, completed under the direction of a faculty mentor. Specific expectations of the research experience to be determined by the faculty. Repeatable for credit. Prerequisite: consent of instructor.

Frequency: Not offered on a Regular Basis  
Repeatable: Yes