Contact department for description.

Contact department for description.

Capstone course requiring application of knowledge and techniques derived from previous courses. Course presents strategic management theories and frameworks, uses integrative cases, and leverages empirical observations to guide students in the formulation of successful firm-level strategies.

Provides an overview of different perspectives and approaches to leadership practice and related organizational behavior topics. Relying on a participative multi-learning approach, the course goes beyond traditional leadership practices to examine empowering leadership approaches for addressing contemporary organizational behavior challenges such as leading teams. The overall objective is to increase students' understanding of and ability to apply contemporary leadership and organizational behavior knowledge in work situations.

The goal of this course is to teach leaders what they need to know in order to build high-performance operations with world-class processes of innovation and continuous improvement. We cover the most current methodologies and tools, together with the most important soft skills required, to create efficient and responsive operations that deliver the highest quality services and products.

This course covers essential concepts and methods to foster data-driven decision-making to motivate business insight and innovation. Lessons cover topics in big data, algorithmic thinking, machine learning, data visualization, and communication. Projects spanning several weeks focus on business problems that can be solved through the application of cutting-edge Data Science techniques. Students develop proficiencies in the use of Python, R, and Tableau by completing regular exercises and projects using real data. No prior programming experience is expected.

This course covers essential concepts and methods to foster data-driven decision-making to motivate business insight and innovation. Lessons cover topics in big data, algorithmic thinking, machine learning, data visualization, and communication. Projects spanning several weeks focus on business problems that can be solved through the application of cutting-edge Data Science techniques. Students develop proficiencies in the use of Python, R, and Tableau by completing regular exercises and projects using real data. No prior programming experience is expected.

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.