Master of Science in Business Analytics Curriculum

Career Management (1.5 Credit Hour)

Explore where the MSBA program aligns with your career aspirations, the various directions data analytics knowledge can take you, and what you need to prepare for these next steps.

Analytics Software Technology (3.0 Credit Hours)

Become familiar with key data management and analytics software and programming languages, including Python. In the process, the course covers techniques for importing data, data manipulation, cleansing, transformation, creating new variables, and introductory data analysis.

Probability and Statistical Modeling (3.0 Credit Hours)

Learn to model uncertainty through probability, decision analysis, simple linear regression, multiple linear regression, and model selection and to assess the underlying assumptions of these mathematical models.

Fall Semester

Starting in late August, the Fall semester consists of a combination of semester-long courses and two mini modules that examine the relationship among data, business analytics, and organizational performance in greater depth.

Intro to Business Analytics Practicum: Assessing Organizational Performance and Managing the Project (1.5 Credit Hours)

Beyond being proficient in business analytics methodologies, success as a business analytics professional requires an understanding of how business analytics supports the broader mission of the organization and its strategy. Given this, this course focuses on the important relationships between data, business analytics, and organizational performance. Additionally, the course addresses topics related to project management and teamwork to prepare students for their Business Practicum.

Practicum I: Mess to Model (1.5 Credit Hours)

Part of a three-course sequence for gaining real-world project-based experience, this class sees students grouped into teams, where they work under the direction of a faculty mentor and collaborate with a corporate partner. In the process, you’ll gain a hands-on understanding of problem scope, data requirements, expected deliverables, the analytics techniques needed to provide results, and leadership principles.

Visual Analytics and Influencing (3.0 Credit Hours)

Understand how to communicate your analyses to all levels of management through data visualizations and learn key principles and techniques for transforming data points into an effective, convincing narrative.

Data Management (3.0 Credit Hours)

Coursework goes through database design and usage concepts. In the process, you’ll learn the latest methods for transforming large amounts of data and become familiar with data manipulation best practices.

Predictive Analytics / Forecasting & Data Mining (3.0 Credit Hours)

Discover how to analyze datasets in greater detail and make predictions through linear and logistic regression, classification, decision trees, clustering, and text mining. While the course touches on theoretical concepts and practical computational skills, you’ll also have the opportunity to analyze and deliver results for real-time datasets.

Prescriptive Analytics (3.0 Credit Hours)

This course covers how to analytically formulate decision problems using decision analysis, optimization, and simulation models. In addition to model formulation and validation, emphasis is placed on how to perform analysis with models to generate insights, benchmarking to estimate impact, and how to effectively communicate results and recommendations to managers.

Spring Semester

Beginning in early January, this semester is divided into two separate modules, during which students continue to develop models for forecasting, optimization, and yielding actionable intelligence and explore multi-industry applications of data analysis. Students also finish the three-course team-based practicum and present their findings.

Business Analytics Practicum II: Model to Insight (1.5 Credit Hours)

During the second stage of this three-part practicum, you’ll continue your team-based project, utilizing modeling and analysis techniques to gather insights and draw conclusions from your corporate partner’s real-time data.

Business Analytics Practicum III: Insight to Impact (1.5 Credit Hours)

The conclusion of the MSBA program’s three-part practicum has student teams communicating their insights and recommendations to a partnering corporate client.

Machine Learning (1.5 Credit Hours)

Machine learning becomes essential for parsing and organizing large volumes of data, be it text, numbers, or images. This course gives you an understanding of the algorithms and statistical models on which machine learning is based and how this artificial intelligence–rooted technology draws out insights from and applies patterns to available data.

Analytics in Society: Security, Legal, Policy, and Enterprise Issues with Data (1.5 Credit Hours)

Big Data isn’t a free-for-all world. In analyzing and collecting data, professionals need to understand key policies and ethics arguments for handling and using such sensitive information. Course topics cover these points in relation to legal, privacy, and security concerns.

Marketing Analytics (3.0 Credit Hours)

Working with market research, you’ll learn to collect, analyze, and interpret this information to make and influence business decisions. Through these processes, you’ll become familiar with Chi-square analysis, ANOVA, Regression, Conjoint Analysis, Discriminant Analysis, Cluster Analysis, and Multidimensional Scaling.

Financial and Risk Analytics (3.0 Credit Hours)

Learn capital budgeting, portfolio models, options pricing, and risk quantification methods to create financial models and assess and manage risk.

Process and Supply Chain Analytics (3.0 Credit Hours)

The focus of this course is on using analytics to improve operational processes as well as how to design an effective supply chain. Topics such as flow analysis, process automation, inventory control, capacity planning, and distribution network design are covered in this course. Emphasis is placed on how to manage the variability in these operational systems.

Note: Program and curriculum are subject to minor changes.