A vendor-neutral course covering the objective of the CompTIA A+ hardware and software exams. This course gives a broad base of knowledge and competency in core hardware and operating system technologies in areas such as installation, preventative maintenance, networking, security and troubleshooting.
3.0 Credits

This course introduces information technology systems and their uses within organizations to support business operations. Topics covered include systems concepts, database features, data warehouses, decision support systems, systems planning and development, networks, and emerging technologies.
3.0 Credits

This course introduces the student to concepts in electronic commerce. The course covers all major ecommerce models including: business-to-business (B2B), business-to-consumer (B2C), consumer-to-consumer (C2C), E-Government and E-Learning. Internet retailing concepts will be introduced. Issues in Internet law, ethics, and cybercrime will be explored.
3.0 Credits

CompTIA Network+ is a vendor neutral networking certification that is trusted around the world. It validates the essential knowledge and skills needed to confidently design, configure, manage and troubleshoot any wired and wireless devices.
3.0 Credits

The application of graphical design principles to the creation of Web sites and applications is the focus of this course. Students will create and edit digital images and graphics that provide aesthetic and functionality to enhance the content they create. Basic types of images used in computer-based communication will be discussed as well as organizing the layout to present compelling content. Topics include wireframing, layout, editing, and usability testing.
3.0 Credits

In today's digital age, the effective management of information systems requires a deep understanding of the legal frameworks governing data privacy, intellectual property rights, cybersecurity, and ethical standards. Students gain a comprehensive understanding of the legal and ethical considerations inherent in the use, management, and development of information systems within organizations as well as personally. Through a combination of theoretical frameworks, case studies, and practical applications, students will gain the knowledge and skills necessary to navigate the complex landscape of information systems law and ethics.
3.0 Credits

This course provides the basic knowledge to plan, implement, and maintain an information security system. Topics covered include threat identification, countermeasures used to mitigate threats, cryptography, wireless and remote access security, and the development of security policies for organizations. This course prepares students to take the CompTIA Security+ Certification exam. (P: CIS 225). Special Fee $1650
3.0 Credits

Project management is the application of knowledge, skills, and tools to implement information systems solutions in an organization. This covers the core areas of project management such as project groups, teams, schedule, cost, quality, risk, communications, resource, procurement, and stakeholder management. Emphasis is placed on the agile development process. Students will complete projects using standard documentation for project managers. (P: CSCI 109 or CIS 129 and junior or senior standing).
3.0 Credits

An introductory survey course in which computers and their consequences are viewed in terms of their historical and societal impact. The course emphasizes principles as opposed to technical training. A range of topics in computer science will be covered including history, application software, programming, artificial intelligence, and the impact of computers on society. This course is appropriate for anyone interested in gaining insight into the discipline of computer science. (P: MATH 107 or satisfactory placement score).
3.0 Credits

An overview of the field of data analytics focusing on business analytics. Topics include data visualization, an overview of statistical methods and predictive analytics (including an introduction to data mining).
3.0 Credits

An introduction to the principles of structured programming focusing on control abstraction. Language elements covered include data types, control structures, elementary data structure, functions, and parameter passing. (P: MATH 107 or satisfactory placement scores)
3.0 Credits

This course provides a laboratory-based introduction to web page design and development. Topics covered include HTML language fundamentals, HTML editors, CGI (Common Gateway Interface) processing, JavaScript programming, and Dynamic HTML. This course is appropriate for all students who wish to develop web pages. Students will be required to complete a major web-based project for the course. (P: MATH 107 or satisfactory placement scores).
3.0 Credits

This is an introductory course in the Python language, a high level computer programming language that has been used at groups like YouTube, Industrial Light and Magic, NASA, and many others, and is one of the three "official" languages at Google. Python is used for scientific applications, game development, desktop applications, graphics, web applications, and other purposes. Its English-like syntax and use of indentation results in very readable code, and it has a large number of standard and third-party libraries that make creating programs for a wide variety of tasks intuitive and often simple. This course will introduce and explore a number of key features of Python, including its syntax, useful modules in the standard library, desktop GUI programming, basic database access, and how to make good use of Python learning resources, including the excellent online Python community. The course assumes no prior programming experience, though it is helpful. (P: MATH 107 or equivalent).
4.0 Credits

An introduction to the principles of structured programming focusing on control abstraction. Language elements covered include data types, control structures, elementary data structure, functions, and parameter passing. (P: MATH 107 or satisfactory placement scores).
4.0 Credits

Advanced study of structured programming focusing on data abstraction and using object-oriented techniques. Language elements studied will foster skill in developing abstract data types. Students will implement and use stacks, queues, and trees to perform a variety of tasks including sorting and searching. Special emphasis will be placed on evaluating the appropriateness of an implementation. (P: CSCI 159).
4.0 Credits

An algebra course at the intermediate level. Topics include fractional equations, graphing, exponents and radicals, quadratic equations, and an introduction to logarithmic and exponential functions. (P: MATH 011 or satisfactory placement score).
3.0 Credits

A course focusing on applications of mathematics that require only basic algebra and arithmetic. Topics include logic and critical thinking, units of measure, percentages, finance and loans, basic statistics and probability.
3.0 Credits

A course for students with an average high school background in mathematics (two years of algebra) who need further preparation before taking Calculus. The course focuses on creating a familiarity with functions that will be encountered in Calculus, especially exponential and logarithmic, trigonometric functions. Not open to students who have earned a grade of C or better in a college calculus course. (P: MATH 107 or satisfactory placement score).
3.0 Credits

Brief review of algebra and trigonometry, limits, continuity of algebraic and trigonometric functions, the derivative and its applications and integration of algebraic and trigonometric functions. (P: MATH 142 or satisfactory placement score).
4.0 Credits

Applications of integration, techniques of integration, improper integrals, L’Hospital’s rule, polar coordinates, infinite series, Taylor series. (P: MATH 181).
4.0 Credits

Descriptive statistics including tables, graphs, measures of centrality and dispersion, percentiles, and scores. Elementary probability including discrete and continuous random variables and the binomial and normal distributions. Inferential statistics including point and interval estimation, parametric tests of hypotheses, simple linear regression and correlation, and some non-parametric tests such as chi-square and sign tests. Lab work with a statistical computer program. (P: MATH 107 or MATH 125, or satisfactory placement score).
3.0 Credits

This course focuses on discrete mathematical concepts that can be applied to computer science and developing skills needed in the study of advanced undergraduate mathematics. Topics include Boolean logic, sets, methods of proof, mathematical induction, asymptotic notation, recurrence relations, basic combinatorics, and an introduction to graph theory. (P: MATH 142 or placement based on high school transcript).
3.0 Credits