Persuasive communication is a vital component to many aspects of business life. This course introduces the basics of communication strategy and persuasion: audience analysis, communicator credibility, and message construction and delivery. Written and oral presentation assignments derive from cases that focus on communication strategy. Students receive feedback to improve presentation effectiveness. Additional coaching is available for students who want to work on professional written communication.

This course is designed to achieve an understanding of fundamental notions of data presentation and data analysis and to use statistical thinking in the context of business problems. The course deals with modern methods of data exploration (designed to reveal unusual or problematic aspects of databases), the uses and abuses of the basic techniques of inference, and the use of regression as a tool for management and for financial analysis.

This course provides an introduction to programming languages and to the software design methods. The programming language of choice is Python. However, the course will introduce the students to the fundamental programming concepts appearing in various other programming languages, including Java and C, that go well beyond the specifics of Python. Upon completion of this course, the students will be able to acquire practical programming skills in Python and understand the principles of structured software development. They will also understand the principles of designing large software systems and what it takes to plan, analyze, design, implement and support large Information Systems throughout their entire System Development Lifecycle.

This course examines challenges specific to entering international markets and conducting marketing operations on an international scale. Topics include identifying and evaluating opportunities worldwide, developing and adapting market strategies to specific national market needs and constraints, and devising and coordinating global marketing strategies. Emphasis is placed on strategic issues relating to international operations rather than on technical aspects of exporting and importing.

This course will change the way you think about data and its role in business. Businesses, governments, and individuals create massive collections of data as a byproduct of their activity. Increasingly, decision-makers and systems rely on intelligent technology to analyze data systematically to improve decision-making. In many cases, automating analytical and decision-making processes is necessary because of the volume of data and the speed with which new data are generated. We will examine how data analysis technologies can be used to improve decision-making. We will study the fundamental principles and techniques of data mining, and we will examine real-world examples and cases to place data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. In addition, we will work “hands-on” with data mining software.

Topics covered:

• Data mining and data mining processes
• Introduction to predictive modeling
• Data fitting and over fitting
• Model testing
• Cross-validation and learning curves
• Model performance analytics
• Unsupervised learning and clustering
• Bayesian reasoning and text classification

The advances in AI, big data and mobile Internet technologies have been making profound impacts on modern retailing and marketing channel management, as evident by the increasing power of tech giants, such as Amazon and Alibaba, in the global retail industry. This course intends to survey key technologies adopted in the new retailing landscape and their strategic implications on marketing decisions and business models, with discussions on topics such as personalized targeting, search and recommendations algorithms and their applications, mobile technologies in retailing and channel management, customer loyalty programs and subscription-based retailing, selling through social media and livestream media, omni-channel management, Internet of things and channel management, managing e-commerce platform and its ecosystem, etc.

This course provides a journey from conventional market research methodologies to the dynamic capabilities of Artificial Intelligence (AI) and Machine Learning (ML). Throughout this course, participants will harness the power of Generative AI to innovate in areas like survey design, social media campaign formulation, and advanced experimental designs. A pivotal focus of the curriculum is on contemporary data applications for market intelligence, encompassing both structured and unstructured data sources. Engage in-depth with predictive algorithms, dimensionality reduction techniques like PCA/Umap, clustering algorithms, and delve into processing eclectic data types such as text, images, and audio. The course underscores hands-on learning, ensuring participants master practical applications through cutting-edge tools and platforms.

Pricing is one of the most important but least understood marketing decisions. This course is designed to equip participants with the frameworks, techniques, and latest thinking on assessing and formulating pricing strategies. We will learn the process of making pricing decisions and explore innovative approaches for setting prices. The emphasis of the course is on ways in which you can help firms in diverse industries to improve their pricing. The topics of discussion include pricing of durable goods, pricing of consumer package goods, pricing of service, pricing of informational goods, new product pricing, price promotions, behavior-based pricing, price bundling, nonlinear pricing, targeted pricing, pricing through a distribution channel, and international pricing etc. Upon successful completion of this course, you will (a) gain a solid understanding of pricing practices across different industries, (b) learn state-of-the-art frameworks for analyzing pricing issues, and (c) master the essential techniques for making profitable pricing decisions with strategic thinking.

This course studies the consumer as a decision maker. It examines social and psychological influences on purchasing decisions, emphasizing their implications for marketing strategy. Topics include the consumer as a decision maker; motivation attitudes and their effect on behavior, information processing, consumer risk, and demographic, social, and cultural influences on purchasing behavior. Applications to advertising, product, and segmentation strategies as well as Web-based applications of consumer behavior are highlighted.

Brand planners/strategists face many challenges, including how to a) create a comprehensive brand architecture that will provide strategic direction, b) Generate motivating brand identities and value propositions for the key brands, c) develop brand-building programs, and d) leverage new technologies. The goal of this course is to provide concepts, models, methods, and role models that will help address these challenges.

The Capstone Project is a for-credit experiential learning course that integrates and weaves together concepts learned from the other constituent courses that comprise the curriculum and links them to practical applications. In small groups starting with pre-work during the Fall semester, students will work together to solve cases presented by companies. 

This course covers the foundational management principles of the advertising business. Through a hands-on project, students will learn how to develop, analyze, and invest in integrated communications programs. Classes will be a combination of textbook curriculum and real-world examples. There will be particular emphasis on the role of advertising in a marketing plan, the promotional mix, strategy and positioning development, creative development, the evolving media landscape, the client agency relationship, and the overall future of the business.

This course focuses on enabling students to analyze and develop sophisticated interactive marketing programs. The primary objectives of this course are a) to introduce students to digital advertising and marketing theories and best practices in digital marketing and b) to give students the opportunity to apply this knowledge to building or improving the marketer’s use of digital media. The course is designed to be a mix of strategic and tactical practice.

This course introduces students to the strategic and practical applications of artificial intelligence (AI) in marketing analytics. Grounded in core marketing challenges, the course examines how AI tools—across descriptive, predictive, prescriptive, and generative categories—can enhance marketing strategies. Students will gain hands-on experience using state-of-the-art AI technologies to solve real-world marketing problems, such as customer segmentation, social listening, churn prediction, A/B testing, and branded content generation.

Beyond technical capabilities, the course emphasizes the strategic choices marketing leaders face when adopting AI systems, including questions of implementation, interpretability, and cross-functional alignment. Students will analyze how AI-generated outputs are perceived by consumers and managers, and evaluate their implications for brand equity, customer trust, and organizational performance. Special attention is given to generative AI's impact on creativity and marketing workflows.

The course also engages students in the ethical, regulatory, and societal dimensions of AI in marketing—addressing challenges such as algorithmic bias, fairness, explainability, and governance. By the end of the course, students will be equipped to lead AI-driven marketing initiatives with both strategic insight and critical responsibility.

Professional Responsibility and Leadership (PRL) is an interdisciplinary course that builds on prior coursework students have completed. In PRL, students pursue the following learning objectives: 1) to reflect on why they are embarking on a career in business, and how they intend to act as business professionals; 2) to think systematically about the risks and sources of resilience relevant to their professional lives; 3) to cultivate the habit of engaging in reflective dialogue with diverse stakeholders. The basic format of the course is a discussion seminar, drawing from three different sources: 1) the students’ own personal experiences and values; 2) expert insights drawn from a variety of academic disciplines (including philosophy, literature, history, and art, as well as the natural and social sciences); and 3) relevant contemporary and historical business cases. PRL focuses primarily on the students’ own interests, refining them through dialogue and in reference to expert sources. 

Professional Responsibility and Leadership (PRL) is an interdisciplinary course that builds on prior coursework students have completed. In PRL, students pursue the following learning objectives: 1) to reflect on why they are embarking on a career in business, and how they intend to act as business professionals; 2) to think systematically about the risks and sources of resilience relevant to their professional lives; 3) to cultivate the habit of engaging in reflective dialogue with diverse stakeholders. The basic format of the course is a discussion seminar, drawing from three different sources: 1) the students’ own personal experiences and values; 2) expert insights drawn from a variety of academic disciplines (including philosophy, literature, history, and art, as well as the natural and social sciences); and 3) relevant contemporary and historical business cases. PRL focuses primarily on the students’ own interests, refining them through dialogue and in reference to expert sources.