Senior Project Capstone Course

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This course provides an introduction to the fundamentals of visual programming as well as procedural language structure and capabilities. Students learn about visual programming development, including problem definition, problem solving and algorithms, procedures, controls, arrays, structures, coding, visual interface design, testing, and debugging.

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This course introduces the principles and practices of Object Oriented (OO) programming. Topics include user interface and problem data classes; class versus instance properties and methods; abstraction; encapsulation; inheritance and multiple inheritance; polymorphism; software design techniques; and problem solving. The concepts are utilized in numerous programming projects.

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Old course name - Web Access and System Design.

Students learn about the influence of e-Business, local and global transaction processing, Internet, web design and development, and Electronic Data Interchange on information systems. After an introduction to the basic concepts of relational database systems, students will practice connectivity to a database to retrieve information. The course includes a design and implementation project involving a database in the Web environment.

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Students in this course examine fundamentals for the development of information processing systems. Topics include requirements gathering, feasibility studies, software lifecycle overview, tools and equipments used by designers, and factors associated with successful systems.

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First of a two course senior project on systems development with a significant laboratory component. Students will design a prototype information system in the context of the project team environment employing methodologies of a model software system life cycle including specification, analysis, and design.

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The second in a two course senior project with a lecture and significant laboratory components. Students implement a prototype information system in the context of the project team environment employing the methodologies of a model software system life cycle. Capstone course for the Information Systems major.

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Old course number for this course was CIS 4510.

Expert systems construction and application. Use of computers in managerial decision making. Examination of problem solving and decision models in relation to the business environment. Practical application emphasizing evaluation of available systems and hands-on experience.

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This is the first of a sequence of two courses where students will have the opportunity to analyze, implement, and deploy complex software systems as enterprise mobile applications, as computer games, and as an appropriate combination of both.

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This is the second of a sequence of two courses where students will have the opportunity to analyze, implement, and deploy complex software systems as enterprise mobile applications, as computer games, and as an appropriate combination of both.

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This course studies the process of integrating different systems and software applications by examining current and emerging trends, strategies, and techniques for developing systems integration solutions effectively. Example topics covered include, but are not limited to: documenting integration requirements using business process models, designing integration solutions reusing patterns, and implementing integration solutions using service oriented architecture. Students will extend course topics via library assignments, programming assignments, tool evaluation assignments, and other assigned activities.

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Website & App Development for Community course provides a community-based learning opportunity. Students will learn the fundamentals of website design and development. Students will develop and deliver a basic website that satisfies the requirements set forth by a community partner. Students will use a content management system to develop the website.

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Previously, this course was named as Interface Design & Implementation.

This course covers issues associated with the design, implementation, and evaluation of human/computer interfaces including interface devices, metaphors, and interaction styles. Topics covered include task analysis; dialog models and examples; user centered design including naive and expert user interfaces; interface development methodologies and implementation tools; interface testing and quality assessment.

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In this course, topics covered include the application of software engineering principles and techniques to the development, deployment, and maintenance of high quality Web-based systems and applications; markup languages, distributed objects, hypermedia and Web integration; architecture and security issues; client side and server side technologies; distributed technologies; data integration across heterogeneous Web sources.

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The aggressive rate of data growth has outpaced our ability to manually understand what data represents. Data is typically stored in database and files, and represented in different formats (structured, semi-structured, or no structure). Data analytics is the science of applying quantitative techniques to analyze data with the objective of discovering hidden knowledge and identifying interesting patterns. This course surveys a number of data preprocessing and sampling methods, data distributions and uncertainty, statistics, regression, time-series analysis, predictions and clustering. It introduces the characteristics and analytic challenges on dealing with clinical data from electronic health records. The course also covers emerging trends in Data Analytics and the applications of information technology in the healthcare. Statistical analyses and data mining techniques will be discussed along with methods for deploying these techniques using the open source tools.

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This course gives a broad overview of the various aspects of data analytics and visualizations. Students will learn ways of accessing data from various sources such as web APIs and repositories, techniques of cleaning data and organizing data for analysis, using analytical methods to solve real-world problems, and create visualizations to aid the interpretation of analysis results. Students will have hands-on training using relevant programming languages, as well as analytics and visualization tools. Over the course of the semester, students will apply lessons learned and use tools trained to produce interactive, web-based visualization projects.