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CS
250
Software Development Lifecycle
Effective methodologies and models are necessary for developing high quality software. In this course, students learn how to identify and apply appropriate software development lifecycle models and methodologies. All phases of activity within the lifecycle, including analysis, design, development, and testing, are explored with an emphasis on the roles of the contributors within each phase. Software development methodologies are examined with a focus on the application of agile processes.
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CS
260
Data Structures and Algorithms
Learn about data structures and algorithms used for analyzing large volumes of data. Focus on common data structure operations, including searches and sorts.
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CS
310
Collaboration and Team Projects
Learn how to collaborate on a software project. Apply appropriate change control and versioning practices. Use technologies for supporting collaboration on a project in a distributed workforce with remote contributors.
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CS
320
Software Testing, Automation, and Quality Assurance
Learn about software engineering testing strategies and practices, and study how software quality assurance techniques are used through the software development life cycle, including requirements analysis, verification and validation, and quality management.
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CS
330
Computational Graphics and Visualization
Provide an introduction to computer graphics drawing algorithms and 2-dimensional and 3-dimensional display techniques. Learn the current software and hardware used for computational graphics and visualization.
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CS
340
Advanced Programming Concepts
Examine current and emerging technologies used to develop software systems. Apply advanced-level programming concepts to solve real-world programming problems. Use various programming technologies or platforms to develop advanced-level programming.
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CS
499
Computer Science Capstone
Taken in the student's final term, the capstone course is the culminating experience for the Bachelor of Science in Computer Science. Integrate previous coursework and practical experience with a focus on authentic demonstration of competencies outlined by the program. Enhance previously submitted programming projects that demonstrates a level of mastery of the stated outcomes of their degree program in computer science.
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DAT
220
Fundamentals of Data Mining
A large portion of data analytics focuses on identifying meaningful patterns in data. Using a case studies approach, students will examine effective strategies that blend both hypothesis testing and data-driven discovery methods to identify meaningful data patterns and apply that knowledge to common business problems. Emphasis will be placed on data-mining tasks such as classification, clustering, and sequential pattern discovery.
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IT
255
Introduction to the Linux Operating System
Introduce students to the major components of the Linux operating system and the basics of the Linux command line. Work with files and directories, archive and compress files, and search and extract data from files using pipes and redirection. Learn how to package Linux commands within a script.
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IT
315
Object Oriented Analysis and Design
This course develops software systems engineering principles combining object-oriented design principles and methods augmented by computer assisted engineering (CASE) technology. The course involves use of the unified modeling language (UML) and, through the vehicle of a student group project, applies these elements to the system development life cycle. This course is writing intensive, as student project teams are required to submit a comprehensive project report and a PowerPoint presentation. Specialized Systems Development Computer Laboratory intensive and open laboratory intensive. Writing intensive course.
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IT
365
Operating Environments
Learn about operating environments used in today's business computing environments, including enterprise level systems down to mobile devices. Gain an understanding of the components in an operating system and how they interact with each other and with system hardware and application software. Explore the importance of writing programs that take full advantage of operating support.
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MAT
230
Discrete Mathematics
Discrete mathematics is the study of mathematical structures that are fundamentally discrete rather than continuous. That is, in contrast to the real numbers that vary continuously, the objects of study in discrete mathematics take on distinct, separated values. Topics include operations on sets, logic, truth tables, counting, relations and digraphs, functions, trees and graph theory. A significant goal of this course is to improve students' critical-thinking and problem-solving skills.
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MAT
350
Applied Linear Algebra
This is a first course in linear algebra and matrices. Topics include systems of linear equations, linear independence, matrices of linear transformations, matrix algebra, determinants, vector spaces, eigenvalues and eigenvectors. After mastering the basic concepts and skills, students will use their knowledge of linear algebra to model a selection of applied mathematics problems in business, science, computer science and economics.
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Elective: Students select 12 credit hours in DAD, DAT, GAM, IT, or ISE with a minimum of 6 credits at the 300 to 400 – level
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