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Required Core Curriculum

 We require the completion of 30 credit hours total, consisting of a 15-hour business core and a 15-hour analytics core and including two courses focused on our corporate-sponsored capstone project. Students learn quantitative modeling techniques for descriptive, predictive, and prescriptive analytics and gain education in data analysis and visualization, principles of finance for business, and modern technologies such as AI, cloud computing, and data mining.

We also focus on teaching "soft skills " — including how to work in teams to diagnose, frame, and solve complex business problems; how to manage employees, navigate human dynamics, and understand organizational behavior; how to run a meeting, create agendas, manage projects, and communicate with executives; how to craft compelling, professional presentations and consulting reports that lead decision makers to take action; and more. Learn more about our core curriculum below.

Please note: some substitutions for business core courses may be made with the approval of the Academic Director.

Summer 2 Session 

Introduction to basic statistical (inference) tools necessary in managerial decision-making. Topics include, but are not limited to, descriptive statistics, elementary probability theory, sampling and sampling distributions, portfolio management, hypothesis testing, regression analysis, quality improvement, and Six Sigma concepts and methodology.

Introduction to your fellow cohort members. We engage in team-building exercises and address a variety of topics, including program expectations, capstone project lifecycle, issue trees, approaches to problem-solving, ethics, and more. This in-person orientation is required for all MSBA-BA students.

Fall Semester

Fundamentals of accounting systems as they relate to decision making. Attention is directed toward accounting for the core of management control and financial reporting systems, and as integrally related to the information system. 

Principles and techniques for information visualization and reporting for business analytics. Covers principles of human perception and application of information visualization software for preparation, exploration, synthesis, interpretation, and presentation of business data to support decision making.

Development of business intelligence and analytics solutions and applications to various types of decision- making problems. Analytics software and techniques. Data preparation, data exploration and visualization, predictive analytics techniques, text analytics, spatial analytics.

This course examines the determinants and consequences of human behavior in formal organizations. The specific graduate focus is on understanding the individual, interpersonal, and group processes which underlie all human dynamics.

Spring Semester

Overview of business intelligence and analytics technologies and their strategic use including defining/framing the business context for decisions, decision models, data issues, business intelligence, building analytics capability, cloud computing, making organizations smarter, and measuring the value of analytics.

Explores the basic concepts underlying the finance function, relevant to finance and non-finance majors. It provides an understanding of the firm's decision-making framework in the context of the economic environment (financial markets) in which the decisions are made. The specific topics covered, at a basic level, include investment decision under uncertainty, valuation, risk and return, market efficiency, portfolio theory, asset pricing, cost of capital, capital investment decisions, and futures and options markets.

Management and execution of business analytics projects. Problem and scope definition, identifying objectives, data requirements and preparation, selection of software tools, project planning and administration, leadership and team building, and assessment of project value and effectiveness.

With the onset of the digital age, marketers are now bombarded with an ever-increasing amount of information. However, many firms lack the expertise to use incoming data to optimize their marketing strategies. Thus, modern marketers need smart and rigorous tools to adapt to fast changes in the marketplace, manage an increasing amount of information, and make better decisions. This course will introduce you to the tools that you will need to make data-driven decisions. We will cover marketing analytics approaches to (1) market segmentation, targeting and positioning, (2) conducting A/B testing, (3) performing data visualization, (4) using marketing mix models to analyze marketing problems, and (5) learning about modern topics such as AI, marketing data platforms and text analysis. The aim of this course is to develop the skills, understanding, and experience required to make intelligent use of marketing data to drive business recommendations and decisions. The course employs a combination of lectures, case studies, and “hands-on” exercises. By the end of this course, you will be able to walk into any company and help make data-driven marketing decisions.

Summer 1 Session 

Management and execution of capstone business analytics projects. Integrated application of analytics knowledge, techniques, and tools resulting in the development and delivery of insights, recommendations, and expected outcomes to corporate stakeholders in professional communications, presentations, and reports.