Online Master of Science in Management Information Systems (MSMIS)

Individual research into an area of information systems. May be an application or theory. A paper must be presented and defended.

This course will enable the student to understand the current state of e-business and follow its new development, identify e-business opportunities and develop business models for such opportunities, and examine the importance of e-shopping, social media, mobile computer, and consumer adoption.

Analysis, design and implementation of information flows for management control and decision making. Use of systems development concepts, principles and practices.

This course introduces modern data systems, which surveys and discusses current business database technology and system management and applications trends as related to business domains. Topics include database management, and operations to ensure data quality for data analytics. The main goal is to not only familiarize students with traditional concepts of data systems, such as relational model and database systems but also focus on modern trends leading the data management industry.

Variable content in the information systems area within the classroom setting. May be repeated up to 6 hours.

An in-depth investigation of the theories, methods, and techniques of various machine learning models. Topics include how artificial intelligence differs from programming; supervised and unsupervised learning models and techniques; validation strategies; data preparation and imputation; organizational, ethical and leadership applications and challenges.

Issues and management techniques involved in administering the information system/resource activities of an organization from a socio-technical perspective. Covers the management of information resources from a strategic and competitive analysis viewpoint.

Theoretical examination of neural networks at the structural level and topological impacts of hyperparameters on deep learning models. An in-depth review of the methods and techniques of various deep learning models as applied to common and novel data sets. Topics include model selection for maximizing performance, theories for generalizing, bias reduction, ethical challenges, and future directions of the field.

This course is designed to expose students to current thinking regarding sustainability and its implications for organizations and their managers. It will cover key issues such as green technologies, hazardous technological material disposal, recycling strategies and other environmental issues.

This course introduces the practical application of business analytics in a variety of contexts. Emphasis is placed on presenting findings to varied constituencies. Key topics to be covered may include predictive modeling and analytics, data visualization, quantitative and qualitative data analysis, and digital marketing analysis. Students will explore the data-driven business decision making through case analyses and a course project with data and software.

This course will examine the process of data preparation, mining methods, and how to mine data using current programming tools. Topics include data selection, cleaning, coding, using different data mining and machine learning techniques, and visualization of the generated structures. Students will develop hands on experience developing supervised and unsupervised data mining algorithms and will learn how to employ these techniques in context of various business applications.

This course will enable the student with how they can use enterprise systems to make the organization more successful. An emphasis is given to supply chain applications, enterprise resource planning systems, and customer relationship management systems.

This course will enable the student to collaborate with a project team to successfully complete a project management simulation, develop the major documents needed to begin an IS project with a real organization, and collaborate with a project team to successfully complete an IS project.

This course will enable the student to use innovation as a competitive situation for organizations, to analyze and critique innovation approaches, create a significant strategic technology policy, and to build a portfolio management office in the government agency or organization.

This course will enable the student to think strategically with respect to using information technology for competitive advantage. Students will use strategic models to align the IS group with the organization and develop an IS strategic plan.

This course will provide the student with the leadership skills of information security management. The course covers managerial and policy topics in information security as well as foundational technical concepts of protection mechanisms, disaster recovery, ethics, regulations and laws.

This course will enable the student to understand how to use technology in implementing the IS strategy for the data storage architecture, data communication architecture, construction, acquisition, use of hardware and software, Internet of Things, cloud computing and technology platforms services.

This course is an introduction to the use of Business Analytics and big data as a strategic resource. A focus is placed on integrating the knowledge of analytics tools with an understanding of how companies leverage data analytics to gain strategic advantage. The key areas of customer analytics and surveys of data mining techniques and applications will also be covered. Case approach is used to emphasize hands-on learning and a real-world view of Business and big data analytics.