Management, Marketing Analytics

Units: 1

Business cases and problems where data analysis is part of the decision-making process. Applications to finance, management, marketing, and operations. Proficiency in Excel methods commonly used in management. Completion of a project where students follow a business problem from formulation to solution using data analysis. Restricted to MBA students.

Offered in Fall Spring Summer

Units: 1

Continuation of a series of business cases and problems where data analysis is part of the decision making process. Estimation of linear relationships among variables, with applications to finance, management, marketing, and operations. Proficiency with Excel methods commonly used for estimation. Completion of a project where students follow a business problem from formulation to solution using the methods covered the course. Restricted to MBA students.

Offered in Fall and Spring

Units: 3

This course is designed around the full analytics lifecycle which encompasses the business problem, the data, the analysis, and the decision. Students will learn to identify and clearly explain business problems that can be addressed with analytics. They will learn to determine which analytic methods are best suited to solve particular problems and clearly explain the results of an analytic model and how those results might impact the business bottom line. Analytical methods to be covered include data, visualization, a review of regression analysis; logistic regression; classification and regression trees [including boosting and bagging methodologies]; and clustering [segmentation] methods. Students will also develop at least a beginning proficiency with several statistical software packages including Tableau, JMP, R, and SAS Enterprise Miner. Emphasis will be placed on analyzing real data and understanding how analytical thinking can be applied to solve big data problems.

Offered in Fall and Spring

Units: 3

This course examines how to collect and process data to make it useful, how to validate, protect, and process data to make it available, and how to create a place to properly store data.

Offered in Fall and Summer

Units: 2

This class will give you the opportunity to explore the ethical issues associated with the development and use of Big Data and data science activities. The data science lifecycle will serve as a backdrop within which to examine ethical concerns related to the design, collection, use and dissemination of data. These include issues of AI and bias, transparency in communications and data design, privacy and data collection, among others.

Offered in Spring Only

Units: 2

Market segmentation, targeting, and positioning. Channels of distribution, promotion strategy, product development strategy, and pricing strategy. Relationship marketing and marketing strategy. Applications in high-tech environments. Restricted to MBA students.

Offered in Fall and Summer

Units: 3

Analytical techniques to convert a wealth of data on customers and markets into insights to guide business decisions. Taking a hands-on and systematic approach on the steps involved in harnessing knowledge from data, the course covers the various data techniques and steps involved in data- and model-driven management decisions. Techniques include market response models, conjoint analysis, discrete choice models.

Offered in Fall and Spring

Units: 3

This course focuses on solving a real-world business problem that includes a heavy data analytic component. The business problem will vary according to the client but could include problems from finance, human resources, marketing, finance, supply chain, or other management areas.

Offered in Fall and Spring

Units: 3

Successful innovation involves creating more valuable experiences for users and customers. The course covers key concepts and methodologies for experience-based innovation, drawing on design and creativity frameworks to fully understand customer experiences. Course activities include exercises and a project to practice innovation and "design-thinking" tools and techniques in a business context. Relevant strategic perspectives for designing innovative products and services are addressed through case studies and other managerial readings with practical business application. The importance of a multi-disciplinary approach to experience innovation is emphasized, such that the course is suitable for students in all disciplines with an interest in innovation.

Offered in Spring Only

Units: 1

This course will discuss artificial intelligence [AI] and its applications to help make data-driven decisions in business and management. Students will learn to understand the language of AI, discuss different applications of AI, and work with actual AI tools at a high level to develop new insights. Hands-on examples will be complemented by applications of AI drawn from different industries.

Offered in Spring Only

Units: 3

Consumer perception of products and brands, including the role of product design and development of consumer attitudes. Analysis of how consumers make decisions and how those decisions can be influenced by messaging, pricing, and emotions.

Offered in Fall and Spring

Units: 3

A systematic approach to structure, implementation and analysis of marketing research for decision making. Models of consumer demand and firm behavior analyzed in a marketing context.

Offered in Fall Only

Units: 3

This course covers the basics of digital marketing from an analytics perspective. Each channel of digital marketing, such as search engine optimization, social, mobile, web, email, and video, are examined and their relationship to overall firm marketing strategy is explored.

Offered in Fall and Spring

Units: 1 - 6

Presentation of material not normally available in regular courses offerings or offering of new courses on a trial basis.

Units: 1

This course explores the use of data analysis techniques and tools that are useful for organizing and categorizing large volumes of information for use by executives to make strategic business decisions. The course exposes students to various Excel techniques through a business case to support management's decision making and focuses on how data analysis can be used to inform management and the board about top strategic risk issues.

Offered in Fall and Spring