MS in Business Analytics Curriculum

3 credits | Prerequisites: None

You work through business problems using descriptive, predictive, and prescriptive analytics in Excel and Power BI. The course focuses on building spreadsheet models, dashboards, and forecasts, and on explaining how those models inform decisions across different business contexts.

Outcome: Build and explain models and dashboards that help others understand what the data is saying and what to do next.

From faculty: The impact of this course is not surrounding rows, columns, charts, or required coursework—it is centered on a way to understand real problems and influence real decisions. In this course, students learn to move from raw data to meaningful analysis, from analysis to clear visualizations, and from visualizations to presentations and dashboards that help people see what matters and decide what to do next. That magical moment happens when a student stops asking, “What chart should I make?” and begins asking, “What story does this data tell, who needs to hear it, and what action should it inspire?”

3 credits | Prerequisites: None

You translate business needs into clear analytics problem statements and shape your findings into structured narratives for a business audience. You develop dashboards and supporting materials, and refine your work through iteration, using executive summaries, technical memos, and presentations to communicate with different audiences.

AI tools are part of the process, used to draft and refine your work while maintaining clarity, accuracy, and judgment.

Outcome: Turn analysis into clear narratives that guide decisions and align stakeholders.

From faculty: I love watching students realize that the storytelling techniques they’ve absorbed their whole lives, from movies and TV to books and journalism, are tools they can use to shape clearer, more compelling data narratives. As we work through real-world scenarios, they see how these methods sharpen their message and strengthen their connection with an audience. As someone who has coached sports for years, I recognize that spark: the confidence that comes from mastering a skill that gives you an advantage. Seeing students reach that point in a world overflowing with AI‑generated noise is as rewarding as watching a team pull off a clean double play.

3 credits | Prerequisites: None

From faculty: This course covers the essential, foundational theories of the various ways data can be structured and restructured, but we do more than talk about conceptual theories—we see them come to life as we put them into practice. Even students who have worked in analytics or data management for years have those breakthrough, “a-ha!” moments seeing the “how and why” behind the best practices of data management.

3 credits | Prerequisites: None

You build and test AI solutions tied to actual business problems. Projects may include customer journey tools, financial models, workflow automation, or internal assistants, using tools like ChatGPT and Excel to explore what is practical, useful, and realistic inside an organization.

The course focuses on evaluating where AI adds value, how to measure its impact, and what it takes to move an idea from prototype to implementation. You also develop a cross-functional AI strategy that considers business goals, operational constraints, and risk.

Outcome: Identify a strong AI use case, build a working prototype, and present a practical plan for implementation.

From faculty: One of the things that makes BUAN 630, Harnessing AI for Competitive Advantage, so unique is that the technology itself is changing almost in real time. The tools, capabilities, and business applications we discuss today may evolve significantly just a few weeks later. That creates a classroom environment built around discovery, experimentation, and adaptation rather than static content.

What I enjoy most is that I get to learn alongside my students. Together, we explore not only what AI can do, but also the broader economic, ethical, and organizational questions surrounding its adoption. Students begin to see that AI is not simply a technology issue. It is a leadership, strategy, and change management challenge that touches nearly every part of business and society.

Watching students grow more confident in navigating these complex questions is one of the most rewarding parts of teaching this course. As new tools emerge and new use cases appear almost weekly, the class becomes an ongoing shared exploration. Being able to participate in that process with students is both energizing and deeply meaningful to me.

3 credits | Prerequisites: None

3 credits | Prerequisite: BUAN 640

You turn business questions into predictive models that support better decisions. The course focuses on building, evaluating, and interpreting models that segment customers, predict outcomes, and identify actionable decision rules using approaches like regression, classification, and clustering.

You learn to communicate results in a way that helps others understand what is likely to happen and what actions should follow.

Outcome: Frame business problems as predictive tasks, build and evaluate models, and translate results into clear, defensible recommendations.

From faculty: Predictive analytics is not just about building a model that performs well. It is about helping an organization understand what is likely to happen next and what to do about it. What excites me about teaching this course right now is that AI has reshaped what this work looks like. Students are often surprised that the hardest part of predictive analytics is no longer the coding. It is deciding what matters, what tradeoffs are acceptable, and how to communicate uncertainty to someone who has to act on the results. I love watching students realize how much further they can take a predictive model when their attention shifts from the mechanics to the impact.

3 credits | Prerequisites: None

3 credits | Prerequisites: 21 credits completed

You work on a live analytics project for a company client, taking responsibility for the full engagement from problem definition through analysis and final recommendations. Working in small teams, you manage the client relationship, navigate ambiguity, and apply the methods and tools developed across the program.

The course is structured as a guided project with regular faculty coaching, giving you the space to do the work while receiving feedback on both your analysis and how you manage the client.

Outcome: Lead an end-to-end analytics project and deliver recommendations that a client can act on.

From faculty: I love watching the moment when students realize they are no longer working on a classroom exercise. They are working with real people, real constraints, and real organizational challenges. The project rarely unfolds exactly as expected, and that is what makes the experience so valuable. Students learn how to adapt, ask better questions, and stay focused when the path forward is not perfectly clear. By the end of the course, many students are surprised by how much confidence they have gained in working through complex business problems as a team.

3 credits | Prerequisites: SEIS 631 and 632 (can be taken concurrently)

Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem.

3 credits | Prerequisites: None

Even the most insightful data analysis has limited value if analysts cannot convey clear, actionable insights to non-technical audiences. This course develops the critical skills necessary to transform complex quantitative findings into compelling data stories and visualizations. Students will learn how to leverage visual design principles that speak directly to human cognitive abilities, guiding business stakeholders toward data-driven decisions. The curriculum covers creating meaningful graphs, reports, and dashboards that improve comprehension, catalyze communication, and enable fact-based choices. By mastering techniques for visualizing and explaining data, students will become adept at distilling analytical conclusions into incisive narratives readily grasped by diverse audiences. Upon completion, they will have obtained hands-on experience with state-of-the-art data visualization tools to generate impactful data-driven visual insights.

3 credits | Prerequisites: SEIS 631 and 632 (can be taken concurrently)

Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem.

3 credits | Prerequisites: None

As project managers, we face impossible schedules, unrealistic specifications and limited budgets. As leaders we face personnel issues, motivation requirements and organizational issues. This course will provide insight and practical examples of the areas of knowledge needed to practice effective project management in today's dynamic work environment. You will learn why similar pitfalls are often encountered with each new project as we examine the chaotic project life-cycle, the complexity people bring to projects and the reasons why our organizations continue to become more chaotic. You will examine the new phase development of project management and use numerous disciplines to create a more dynamic and flexible project management methodology, including: industrial behavior, psychology, human behavior, chaos and complexity, organizational behavior, and systems theory.

3 credits | Prerequisites: None

This course will introduce students to principles that effectively link storytelling to influencing business outcomes ethically and effectively. Our business culture demands concise and meaningful communications that can both inform and influence decision makers. This course is designed to teach business professionals principles and skills that enhance their thinking about data and the use of a variety of communications channels to facilitate positive business decisions. Students will explore the meaning of information and its effect on organizational strategy and culture; be able to build a structured thinking process to tell a compelling story; and gain skills in confidently understanding and using information to influence outcomes.

3 credits | Prerequisites: OPMT 600; Recommended: OPMT 605

There is growing demand for marketers with the technical skills needed to make use of data to inform marketing decisions. Students will work hands-on with marketing data as they learn how to use the tools (mainly R, some Excel) and methods necessary to develop useful customer insights. Students will also learn what marketing questions – segmentation, customer lifetime value, etc. – these methods are meant to address. This course is quantitatively oriented, and some of the methods will be very technical. But these methods are means to an end: to better understand our customers in order to make informed marketing decisions.

1.5 credits | Prerequisites: MKTG 625 or MKTG 600

Digital Marketing continues to rise and has become core to marketplace success. This course provides an overview of how Digital Marketing can be engaged to significantly contribute to achievement of business goals and priorities. This course examines the concepts, strategies and applications related to Websites, Display Advertising, Search, Email, Social and Mobile Marketing with an explicit focus on how each area can be utilized to acquire and strengthen customer relationships across the customer life cycle.

1.5 credits | Prerequisite: MKTG 774

This course offers a hands-on understanding of how to set up, monitor and optimize the effectiveness of Digital Marketing campaigns in alignment with business goals and objectives. Students will learn to use of state of the art Digital Marketing Analytics tools such as Google Analytics and Adobe Analytics for daily analysis as well as prepare dashboards for sharing periodic results with executives, peers and staff.

3 credits | Prerequisites: None

This course will provide an overview of the basic principles of supply chain management, giving students an understanding of supply chain processes from sourcing to finished goods and customers to suppliers, identifying the core supply chain processes. Students will learn the key mechanisms of how companies manage internal processes that control the flow of inventory in the supply chain.

3 credits | Prerequisites: None

In today’s rapidly-evolving global supply chains, managing the complexities of logistics requires more than just theoretical knowledge – it demands real-world experience. Focusing on experiential learning, this course uses an industry leading supply chain simulation, artificial intelligence, case studies, and interaction with industry experts to learn fundamental components of logistics while also developing ways to optimize supply chain operations. Integrated throughout the course is a focus on sustainability, exploring environmental, social and governance issues within the world of global supply chain. Based on real-world examples, the course helps students to gain an understanding of strategic, tactical and operational impact on the supply chain

3 credits | Prerequisites: None

Lean Six Sigma is a course designed to promote an understanding of two popular international methodologies – Lean and Six Sigma. A brief overview of the origin and definition of each will then be followed by an extensive review and understanding of concepts, principles and tools. Through lecture, group discussions, hands-on simulations, team exercises and guest speakers, students will develop knowledge of the inter-relationship of these two methodologies and how to implement for product and process improvement in all types of organizations and throughout all functional areas. Soft skills will also be covered such as working with cross-functional teams, driving organizational change and leading in a Lean Six Sigma culture. This course will not include the use of any statistical analysis tools. This course will provide a framework for students who plan to pursue Lean or Six Sigma certification.