In an era of AI driven digital transformation redefining how work gets done, project risk management skills are in increasing demand. With staggering rates of failure on digital transformation projects plaguing modern organizations, it is essential that we learn to understand project risk management if we hope to reverse this troubling trend. This course examines frameworks that may be applied to many projects, programs, and portfolios to scale risk management best practices. Through evaluating real world examples in various case studies, students are introduced to organized and practical approaches to manage project risks, subsequently delivering enhanced value to customers and stakeholders. This course reviews concepts of risk identification, impact analysis, risk response planning, and risk monitoring & control at the portfolio, program, and project levels.

This course provides an introduction as well as hands-on experience in data visualization. Students will learn how to leverage data visualization for exploration and analysis. Students will be introduced to design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making. We will explore storytelling through a variety of mediums, including presentations and dashboards.

This course provides an introduction as well as hands-on experience in data visualization. Students will learn how to leverage data visualization for exploration and analysis. Students will be introduced to design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making. We will explore storytelling through a variety of mediums, including presentations and dashboards.

Supply chain constitutes a core competency, spanning most business functions required for the delivery of products and services to consumers. Advances in information technology and analytics facilitate continued improvement in supply chain infrastructure and operations efficiency. This course will introduce fundamental concepts in supply chain management, IT-enabled supply chain operations, procurement management, production planning, inventory management, and logistics and transportation. The course involves the use of Excel to support decision making, the study of selected business case studies, and the use of a team-based supply chain simulation game.

The course prepares students to consider the application of AI in business. Students will learn to use standard machine learning (ML) models in Python, and understand how to apply them across a range of business functions. Students will propose and implement a ML project.

The course prepares students to consider the application of AI in business. Students will learn to use standard machine learning (ML) models in Python, and understand how to apply them across a range of business functions. Students will propose and implement a ML project.

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.

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.

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.