Skip to main content


Curriculum – MSBA

The Master of Science in Business Analytics curriculum blends technical skills, such as R and SQL, analytic frameworks for interpreting data, and business acumen for translating insights into actions.

The future of business leadership relies on data-driven decision making. As such, the MSBA curriculum is designed to allow students to gain the business knowledge and analytical skills necessary to develop effective strategies and decisions. From operations and finance, to programming and modelling, to machine learning and artificial intelligence, this is an integrated, comprehensive curriculum for business intelligence.

Highlights

Business Principles

Overview of key management principles from each facet of an enterprise, including Finance, Accounting, Marketing, and Operations.

Leadership Essentials

Business leadership essentials that build a solid foundation for effective data-based decision making, including Competitive Strategy, Leadership, and Negotiations.

Data Analytics Skills

Cutting-edge data analytics skills, including Probability and Statistics, Programming, Data Management and Visualization, and Machine Learning and Artificial Intelligence.

Practical Experience

Practical experience through hands-on projects with Seattle companies, and guest lectures from practicing experts in the field.

Courses

The MSBA curriculum consists of 45 credits taken over four quarters.

BUS AN courses at-a-glance: 45 credits

BUS AN 500: Finance and Accounting (3 credits)
BUS AN 501: Negotiations (2 credits)
BUS AN 502: Leadership and Professional Development (2 credits)
BUS AN 503: Competitive Strategy (2 credits)
BUS AN 504: Marketing Fundamentals (3 credits)
BUS AN 505: Marketing Strategy and Channel Management (3 credits)
BUS AN 506: Operations and Supply Chain Management (3 credits)
BUS AN 507: Spreadsheet Modeling (2 credits)
BUS AN 510: Probability and Statistics (2 credits)
BUS AN 511: Programming Essentials (2 credits)
BUS AN 512: Data Management and Visualization (2 credits)
BUS AN 513: Customer Analytics (3 credits)
BUS AN 514: Analytics for Firm Decisions (3 credits)
BUS AN 515: Digital Marketing (3 credits)
BUS AN 516: Operations Research Data Analytics (3 credits)
BUS AN 517: Machine Learning Methods and AI (3 credits)
BUS AN 599: Business Analytics’ Leader Series and Practicum (5 credits)

Summer quarter

BUS AN 503: Competitive Strategy (2 credits)

This course focuses on students’ ability to think as practicing executives, provide practice in analyzing, evaluating, and modifying organizations’ strategies while considering the changing conditions in the economic, technological, political/legal and social environments, and operate as a generalist in a corporate setting. Broadly, the course will focus on the context within which the decision maker operates, the pressures of performance, and both the personal and professional limitations of the individual executive as he or she tries to manage effectively.

BUS AN 502: Leadership and Professional Development (2 credits)

This course focuses on the importance of leadership in the role of a business analytics professional. It covers the various approaches that can be pursued to accelerate leadership development, and the proven behaviors that effective leaders exhibit. With contemporary leadership models as the organizing framework, the course reviews practical tools with guided self-reflection to assess students’ leadership skills and develops a plan for students’ leadership development.

BUS AN 507: Spreadsheet Modeling (2 credits)

This courses focuses on the basics of spreadsheet modeling. Spreadsheets and simple models implemented in spreadsheets are the initial step in modeling data. The course covers typical spreadsheet modeling problems and equips students with the tool necessary to start business analytics projects.

BUS AN 510: Probability and Statistics (2 credits)

This course reviews the uses of statistical tools to present, analyze, and interpret data and emphasizes applications of statistical tools and their uses for organizational decision-making, not the theoretical bases of statistical tools. Students will develop data and analysis skills to apply in other courses, work experiences, and life experiences.

BUS AN 511: Programming Essentials (2 credits)

This courses provides essentials necessary for business analytics professional in terms of software and programing skills. Students will learn how to use software such as R, Python and others to 1) Manage and prepare data and 2) Implement models to analyze data.

BUS AN 512: Data Management and Visualization (2 credits)

This course will introduce students to SQL and the basic elements of data management and visualization.

Autumn quarter

BUS AN 500: Finance and Accounting (3 credits)

This course provides a broad introduction to the use of financial information to make decisions within an organization. The course will cover topics that are most useful to managers who are (or will be) in business analytics roles.

BUS AN 504: Marketing Fundamentals (3 credits)

This course provides a broad introduction to marketing decisions within an organization. Marketing is an organizational philosophy and a set of guiding principles for interfacing with customers, competitors, collaborators, and the environment. The course will cover topics that are most useful to managers who are (or will be) in business analytics roles.

BUS AN 505: Marketing Strategy and Channel Management (3 credits)

This course covers marketing with a focus on marketing channels and strategic partnerships. It introduces the notion of Marketing Analytics with decision making based on quantitative analysis and empirical evidence.

BUS AN 513: Customer Analytics (3 credits)

This course focuses on the firm’s interaction with its customers and how data can be used to improve these interactions. Targeting and personalization are the core concepts of modern customer-centric marketing. This course will provide students with the tools and methods that will allow leveraging data to help shape customer relationship.

Winter quarter

BUS AN 501: Negotiations (2 credits)

This course provides a broad array of negotiation skills that are needed for business analytics solutions to be accepted and implemented. The course allows participants the opportunity to develop these skills experientially and to understand negotiations in useful analytic frameworks.

BUS AN 506: Operations and Supply Chain Management (3 credits)

This course provides a broad introduction to Operations Management (OM), the design and management of the processes that transform inputs into finished goods or services. The objective of this course is to provide students with a solid foundation in the models and principles that are necessary to generate improvement ideas.

BUS AN 514: Analytics for Firm Decisions (3 credits)

This course focuses on how firms can use data analytics to optimize their marketing mix decisions or the 4 Ps – Product Design, Pricing, Promotion and Advertising, and Placement. In the process, students will also gain expertise in methodologies for developing statistical models for descriptive, causal, and predictive models for large-scale data.

BUS AN 516: Information Systems Data Analytics (3 credits)

This course focuses on business analytics problem and techniques from an operations research perspective. Many firms in a variety of industries use these techniques and these techniques are applicable to the many functional areas of business, such as operations, marketing, accounting, finance, etc.

Spring quarter

BUS AN 515: Digital Marketing (3 credits)

The course is designed to help students understand the digital marketing landscape using quantitative methods. The goal of the course is to introduce some of the core concepts of digital marketing, and to use a quantitative approach to develop optimal marketing strategies. This course equips students with a solid analytical foundation to evaluate digital opportunities, marketing strategies, and online business models.

BUS AN 517: Machine Learning Methods and AI (3 credits)

This course will introduce a theoretical and practical understanding of core artificial intelligence and machine learning concepts and techniques; and provide hands-on experience in applying these techniques to practical real-word business problems. The course will cover general concepts and techniques including inductive learning, knowledge representation, reinforcement learning, recommendation systems, artificial neural networks, and natural language processing.

BUS AN 599: Business Analytics’ Leader Series and Practicum (5 credits)

Provides the capstone learning experience. Includes seminars given by business analytics leaders and provides students the opportunity to complement their in-class learning experience with practical experience through an industry project.