This course provides an executive viewpoint of marketing concepts, such as branding and segmentation, for strategic and organizational decision-making. There is an emphasis on tools available for analysis and control of marketing activities, including the use of new media. Topics also include industrial life cycles, customer experience, and pricing strategy.

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 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 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.