This graduate course provides comprehensive coverage of project management, focusing on the methods and competencies needed to effectively manage projects. Upon successful completion of this course, students will be able to understand different project management techniques, terminology and trends; define project success measures and methods; improve quality, cost and efficiency with the project management process; and gain basic competency using project management software.

This graduate course provides comprehensive coverage of project management, focusing on the methods and competencies needed to effectively manage projects. Upon successful completion of this course, students will be able to understand different project management techniques, terminology and trends; define project success measures and methods; improve quality, cost and efficiency with the project management process; and gain basic competency using project management software.

This graduate course provides comprehensive coverage of project management, focusing on the methods and competencies needed to effectively manage projects. Upon successful completion of this course, students will be able to understand different project management techniques, terminology and trends; define project success measures and methods; improve quality, cost and efficiency with the project management process; and gain basic competency using project management software.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course reviews the foundations of modern economics with an emphasis on its applications in business. Course coverage includes a range of both microeconomic and macroeconomic subjects. Topics include demand and supply analysis, consumer theory, theory of the firm, unemployment, inflation, monetary and fiscal policy, economic growth, the causes and consequences of recessions, and issues in global economics.

Basic concepts, principles, and practices involved in financial budgeting, planning for the cost of capital, and managing financial aspects of organizational sustainability and growth. Both theory and techniques applicable to financial problem solving.

This course provides an understanding of the strategic role of Information Technologies (IT) in business; how to successfully integrate IT into the organization; how to manage the challenges associated with conceiving, justifying, implementing and maintaining IT-based initiatives ; and how to be an active and productive participant in management decisions that involve IT.

This course provides an introduction to programming with a focus on business and analytics applications. The curriculum supports the development of skills in data extraction and manipulation as well as automating data analysis tasks. Students will become adept in the use of important libraries and will be able to use trusted open-source resources to support continued development of programming skills. No prior programming experience expected.