Graduate Commerce

Global Strategy and Systems provides an overview of global business from both a strategic process perspective and the organization as a system. It introduces a broad conceptual framework involving strategic and critical thinking, business planning, and general management functions. It provides a foundation for the other core modules that develop more specific concepts and techniques. Restricted to MS in Commerce students.

This course covers the use of cost data in strategic planning and control to facilitate the development and implementation of business strategies. Restricted to MS in Commerce students.

Financial Accounting incorporates the perspectives of accounting, corporate finance, and economics to help students understand financial statements and the judgments and incentives underlying accounting choices. The course will use an integrated, cross-disciplinary view of financial reporting and will include major accounting topic including assets, liabilities, equity, off-balance-sheet financing, measurement issues, valuation, and the analysis. Restricted to MS in Commerce students.

Marketing and Quantitative Analysis introduces the marketing management processes that can be applied to various global markets. Topics include understanding market metrics, consumer market dynamics, consumer behavior and social/cultural trends, organizational buying behaviors, market segmentation, global branding, management of goods and services in diverse markets, and marketing decision systems. Restricted to MS in Commerce students.

Organizational Behavior examines human behavior both within the organization and within the global business environment. It discusses personal effectiveness and interpersonal skills in a global climate. Topics include cross-cultural differences, global and virtual teams, leadership, conflict resolution, decision making, creating high-performance teams. Restricted to MS in Commerce students.

Financial Management covers basic corporate finance including cost of capital, capital budgeting, valuation of stock and bonds, working capital management, and international finance. Prerequisite: Restricted to MS in Commerce students.

GCOM 7140 is a research-oriented class that examines how firms can leverage customer analytics to successfully create, manage, and grow brands. The class provides marketing managers and operational business leaders with the analytical tools to develop and operationally execute brand strategies that enhance customer engagement and loyalty.

Consumer Behavior and Pricing Strategy integrates our understanding of consumers from research in marketing, psychology, and behavioral economics. We will take the perspective of a marketing manager and employ this knowledge to develop, execute, and implement effective marketing strategies. Prerequisite: M.S. in Commerce students only

This course will expose you to the knowledge and skills required of, 1) brand managers as they successfully launch and manage branded products/services over time, and 2) brand consultants who consult brand managers on the best strategies and techniques for managing brands. You will also learn the process for conducting a brand audit through a group semester project.

Examines ways to design, develop and execute effective integrated, web, and social marketing programs. The course uses a business planning model which allows students to justify, build, and execute social and digital marketing programs with bottom line ROI. Students learn to identify and measure high value market segments, use web and social research to evaluate competitors and convince management of the value of digital and social marketing.

Developing innovative products is the lifeblood of the firm, yet many product introductions fail due to improper design, unrealistic expectations or a failure to understand the consumer. This course will dissect the new product development process, including creative ideation, concept testing, prototyping, and entry strategies. Concepts such as open source innovation, disruptive technologies, and the diffusion of innovations are also considered.

Through labs, assignments, and a capstone project, students build, evaluate, & deploy predictive ML/AI models using low-code technologies and learn how to apply these concepts to create value & support real-world applications. Students will also learn managerial considerations employing analytics initiatives to create business & societal value. No prior experience with coding, machine learning, or AI is assumed or expected.

This course aims to provide students with a practical understanding of Artificial Intelligence technology. It covers key factors for the successful development, deployment, and management of AI, machine learning, and other algorithmic approaches to automated decision-making. Students will better understand the societal impacts of AI, ethical considerations in the use of AI, the limitations of AI, and approaches to balance AI risks and benefits.

The course provides an overview of the fundamentals necessary to conduct data analytics with Python including understanding Python objects, data types, structures, packages, and data flow statements; and, reading, writing, manipulating, and plotting data. Students will perform predictive analytics via machine learning using industry-standard packages.

Students will learn how to communicate effectively with data and data structures. This includes how to evaluate potential sources of data, aggregate data values from multiple sources, and compile creative, professional, and descriptive visualizations from that data. Students will learn the best type of chart or figure for different situations and how to format those visualizations to maximize the impact to the viewer.

Provides an overview of the concepts, technologies, and tools necessary to support and improve electronic commerce, with emphasis on tools and methodologies for measuring and enhancing digital presence. The two major areas covered are web analytics and search analytics. Through a semester-long group project, the course focuses on how these concepts can be used to measure, analyze, and improve user experience, web traffic, and conversion rates.

Multivariate statistics training to analyze Big Data sets. The course covers discrete choice modeling (logistic and probit models), classification techniques (discriminant and cluster analyses), data reduction techniques (factor analysis), and advanced predictive techniques (regression models with interactions and curvilinear effects, structural equation modeling, and factorial ANOVA). Trains students on IBM-SPSS, SAS, and R.

The primary objective of Project Management is to provide a blend of theoretical knowledge and practical skills necessary for the effective management of projects. To this end, the course is closely tied to the Project Management Body of Knowledge (PMBOK, as espoused by the Project Management Institute) and consists of seminars on such topics as planning, stakeholder management, human resource management, global/virtual teams, risk management. Prerequisites: Restricted to MS in Commerce students.

This course provides students with an introduction in how to effectively fill the role of Project Manager. It covers a blend of conceptual knowledge and practical skills necessary for the effective management of complex projects.

This course is designed to provide a broad overview of management consulting and other related advisory services professions while also helping students develop skills that are broadly applicable in these professions as well as in other fields (business, politics, not-for-profit, etc.). Working both individually and in teams, students will gain an appreciation of what makes consulting and advisory services unique from other areas of business.

This course is focused on harnessing the power of unstructured data to perform advanced analytical techniques. Students will be exposed to big data technologies (NoSQL, Hadoop, etc.) to understand how to manage and interact with large, complex data sets. We will also cover various analytical and machine learning techniques that can apply to these data, with particular attention to text data from reports, articles, and social media.

This course provides a manager's view of cybersecurity and privacy that contains an overview of methods for managing and mitigating cybersecurity risk in organizations. Further, this course includes an emphasis on applying analytics to understand cybersecurity threats. The course will also explore the role of privacy in society.

This course is first in a two-seminar sequence that introduces students to the science and business of the biotechnology industry. The course will explore cutting edge translational research that is shaping current commercialization and industry trends. Students will engage directly with primary research literature and learn from leading scientists and industry executives. Example topics include AI, gene editing/therapy, precision medicine, tissue engineering, biomanufacturing, synthetic biology.

This course is second in a two-seminar sequence that introduces students to the science and business of the biotechnology industry. In addition to continued exploration of translational research, this course will focus on deeper scientific and commercialization topics specific to the industry, including operational and financial perspectives across all stages of organizational maturity. Students will learn from industry leaders who are commercializing, analyzing, and investing in biotechnology.

This course focuses on how to successfully commercialize breakthrough technologies that have high potential to generate social and/or economic value. Issues related to identifying market needs and potential, developing commercialization plans, and understanding business models and entrepreneurial strategy are covered. As an introduction, this is not an appropriate course for students who minored in or have a strong foundation in entrepreneurship.