BAN 610. Statistical Foundations for Applied AI And Business Analytics.3 Credits.
This course covers fundamental concepts in data analysis, statistical reasoning, and their connection to applied artificial intelligence in business settings. Students learn to organize, visualize, and summarize data, measure variability, and work with key concepts such as probability distributions, sampling, confidence intervals, hypothesis testing, regression, and correlation. Experimental design, analysis of variance, and statistical inference are also covered. Throughout the course, students gain hands-on experience with analytics platforms and utilize statistical methods supported by AI-driven tools for decision-making. Students will interpret results, communicate insights, and apply a range of techniques and AI-supported approaches to guide business decisions.
Prerequisites: None
Offered: Every year, All
BAN 615. Predictive Business Analytics.3 Credits.
This course examines predictive modeling and analytics in data-rich business environments, emphasizing the use of applied AI. Students set business objectives, select and prepare data, and design, build, evaluate, and implement predictive models for practical applications such as marketing, customer retention, delinquency and collection analytics, fraud detection, and insurance. Techniques covered include classification and regression decision trees, neural networks, linear and non-linear regressions, and pattern discovery. Through hands-on projects with a range of AI-enabled platforms, students gain experience in applying these tools, interpreting the results, and communicating insights for effective organizational decision-making.
Prerequisites: Take BAN 610.
Offered: Every year, Fall and Spring
BAN 621. Data Management.3 Credits.
This course covers both operational and analytical databases, emphasizing their role in supporting day-to-day business operations and strategic AI-driven analytics. Students design, implement, and manage databases, as well as extract and analyze data for decision-making. Through hands-on assignments, students work on a real-world project with contemporary tools and techniques. They gain skills in creating and maintaining data structures that form the foundation for applied AI solutions, ensuring data quality, and aligning data management practices with organizational goals.
Prerequisites: None
Offered: Every year, Fall and Spring
BAN 629. Text Analytics.3 Credits.
This course extends data mining methods by focusing on text extraction and mining in business contexts. Students explore techniques such as efficient text indexing, document clustering and classification, information retrieval models, and scenario detection. They also enhance structured data by integrating textual data into predictive models. Through hands-on exercises using AI-based text analytics platforms, students gain practical skills for uncovering insights from large text datasets and applying these insights to support business decisions.
Prerequisites: None
Offered: As needed
BAN 650. Data Visualization for Managers.3 Credits.
This course provides an introduction and hands-on experience in data visualization, emphasizing the role of AI-driven tools in creating clear and meaningful displays. Students demonstrate fundamental design and evaluation principles to visually represent both quantitative and qualitative data. Techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical, and network/graph-based data are covered. Students explore how AI can help automate tasks, identify patterns, and support informed decision-making when presenting data to stakeholders.
Prerequisites: None
Offered: Every year, Fall and Spring
BAN 660. Optimization.3 Credits.
This course focuses on developing computational methods to solve various business optimization problems. Students will formulate and solve a variety of optimization problems including linear, integer, mixed- integer, and non-linear. The course also covers understanding decision making under uncertainty
Prerequisites: None
Offered: As needed
BAN 661. Web Analytics and Web Intelligence.3 Credits.
This course focuses on the analysis of a variety of web metrics including tracking, traffic and visitor behavior, tactics and strategies to successfully market on the Web to make data-driven decisions. Business analytics tools and techniques are utilized to extract and analyze web-scale data to guide strategic decision making. Topics address solutions for measurably higher leads, sales, brand recognition, customer satisfaction or lower service costs.
Prerequisites: Take BAN 610.
Offered: As needed
BAN 663. Business Data Analytics with R.3 Credits.
Students learn to program and use R for effective data analysis. Reading data, accessing R packages, writing functions, debugging, profiling code and organizing and commenting code also are covered. Working examples of topics in statistical data analysis are provided. The course also addresses installation and configuration of software as necessary for a statistical programming environment.
Prerequisites: None
Offered: As needed
BAN 664. Health Care Analytics.3 Credits.
This course provides a foundation on data analytics in health care and an understanding of the main concepts and issues. Contemporary tools and technologies are applied to develop an analytics solution to selected health care problems.
Prerequisites: None
Offered: As needed
BAN 665. Big Data and Hadoop.3 Credits.
The concept, principles, issues and techniques for managing Big Data information management resources are covered. The course explores how Big Data fits into an organization's information management strategy. Focus is on the Hadoop platform, emphasizing how it is used to design and maintain Big Data to support analytics.
Prerequisites: None
Offered: As needed
BAN 667. Design and Analysis of Business Information Systems.3 Credits.
This course considers systems-development methods, analysis and design techniques with a focus on object-oriented analysis and design. The application of systems analysis and design concepts using current tools, techniques and approaches is covered. Students engage in hands-on learning and work in teams to complete a real-world project using contemporary analysis and design methodologies and tools.
Prerequisites: None
Offered: As needed
BAN 668. Python Programming for Data Analysis.3 Credits.
This course introduces Python programming with a focus on data analysis and applied AI in business contexts. Students use Python for text analysis, data acquisition and cleaning, and statistical analysis. Through hands-on projects, students gain experience applying AI techniques to interpret complex datasets and support data-driven decisions in business scenarios.
Prerequisites: None
Offered: Every year, Fall
BAN 669. Project Management.3 Credits.
This course develops a foundation of concepts and solutions required for successful completion of a project. Topics include planning, scheduling, controlling, resource allocation and performance measurement.
Prerequisites: None
Offered: As needed
BAN 671. Fundamentals of Blockchain Technology.3 Credits.
This course equips students with tools to integrate and utilize blockchain solutions in business ecosystems while assessing their business value. Private and public blockchain frameworks as well as interconnected devices are analyzed. Blockchain technologies and their ongoing technical challenges are covered. Students work to analyze what problem(s) blockchain technology address, how it solves them, and how to assess new blockchain protocols.
Prerequisites: None
Offered: Every year, Fall
BAN 672. Applied Business Analytics W Advance Exc.3 Credits.
Advanced features in Excel are utilized to create business solutions. This includes working with financial, logical, and statistical functions, as well as Developer, macros, data management, and charts and graphs. Business Intelligence tools, such as Data Queries and Models, What If analysis and Power Pivot are featured. These techniques are applied to business problems and opportunities.
Prerequisites: None
Offered: As needed, Summer
BAN 673. AI and Analytics in Healthcare.3 Credits.
This course provides an understanding of the concepts and issues for artificial intelligence (AI) and analytics within the health care industry. Contemporary tools and technologies are applied to develop AI and analytics solutions for health care problems.
Prerequisites: None
BAN 674. Generative AI Applications in Business.3 Credits.
This course explores the practical use of generative AI tools in business environments. Students will engage with technologies such as ChatGPT, Claude, DALL-E, and others to understand their capabilities, applications, and limitations. The course emphasizes hands-on experience with generative AI to create content and improve existing workflows. By the end of the course, students will have hands-on experience with leading generative AI tools, understand their business applications, and critically analyze their limitations and ethical challenges.
Prerequisites: None
Offered: Every year, Fall
BAN 675. Special Topics.3 Credits.
Prerequisites: None
Offered: As needed
BAN 688. Business Analytics Independent Study.3 Credits.
Prerequisites: None
Offered: Every year, All
BAN 690. Business Analytics Capstone.3 Credits.
The capstone course in the MSBA program is designed to enable students to directly utilize what has been learned in the tools and applications courses to analyze and offer solutions for a major business challenge. A definition of the problem, analysis of options and a comprehensive presentation of findings and solutions are required components of the course.
Prerequisites: Take BAN 610, BAN 615, BAN 621, BAN 650, BAN 668.
Offered: Every year, All