21 courses with the subject BUAN, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
BUAN 044Business Analytics I1.5
This course covers the basic concepts of data, including the collection, organization, exploration, and understanding of data with an emphasis on complex business data. The focus is on data as an organizational asset, and how data is structured for use in business to optimize business decisions and processes. Students will implement data analytic techniques through hands on programming.
This course covers techniques and algorithms for creating effective visualizations of complex business data. The emphasis will be on the use of data visualization in business decision making. Students will implement data analysis and visualization through hands on programming and visualization tools. Prerequisites: (BUAN 044 or BIS 044) and (ECO 045 or MATH 231 or ISE 121)
This course focuses on the application of analytics to decision-making in the context of sports, including on-field and off-field operations. Three categories of decisions will be considered: (1) measuring and predicting player/team performance, (2) decision-making and strategy in sports, and (3) sports program management. Methods from all aspects of business analytics, including descriptive, predictive and prescriptive approaches, will be demonstrated in the context of sports. Emphasis will be placed on interpreting and communicating analytical results to key constituencies. Prerequisites: BUAN 044 or (CSE 003 and CSE 004) or CSE 007 or CSE 012
This course prepares future leaders and managers to leverage artificial intelligence (AI) as a catalyst for creative and innovative problem-solving. Students develop the mindset, skillset, and toolset required to recognize, frame, prioritize, and address complex business challenges using AI-enabled frameworks. Through structured individual and team-based processes, participants apply AI tools to analyze data, design prompt-driven solutions, and explore agent-based approaches. Live case studies across industries provide hands-on experience applying these frameworks in real-world business contexts.
This course offers a dynamic introduction to Generative AI in business, tailored for non-technical students. Using a no-code approach, students will learn Generative AI concepts, practical business applications, and prompt engineering. The course also addresses the ethical implications of AI, empowering students to use GenAI tools effectively and responsibly. This course prepares students for future careers and lays the foundation for understanding Generative AI. Prerequisites: BIS 111
This course focuses on the application of concepts and methods from analytics to problems encountered in real-world sports management settings. Students will work in teams and engage with a client organization to collect and analyze data in a sports-related setting with the objective of addressing a relevant problem and providing actionable insights or implementable solutions. Students will gain experience in communicating to stakeholders and key constituencies regarding data, analysis, results, and recommendations. Prerequisites: MGT 386 and BUAN 304
This class is designed to introduce students to the processes involved in acquiring, cleaning, arranging, analyzing, and visualizing business data using the Python programming language. It will be fast-paced, but assumes only a basic familiarity with coding, and requires no specific expertise in Python to start. Students cannot receive credit for both BUAN 346 and BIS 446. Prerequisites: BIS 111 or BUAN 044 or BIS 044
The course covers theories and practices in predictive analytics in business. Students will have hands-on experience on analyzing business data for business intelligence and improved business decision making. Includes: key theories, concepts, and models of predictive analytics; and data mining tools to formulate and solve business problems. The course uses data analytics software and real data. Topics include prediction, forecasting, classification, clustering, data-visualization and data reduction techniques. Not available to students who have credit for BIS 448 or BIS 456. Prerequisites: (BUAN 044 or BIS 044) and (ECO 045 or MATH 012 or MATH 231)
This course covers advanced analytic methods for understanding and solving business problems. The emphasis is on understanding and applying a wide range of modern techniques to specific decision-making situations. Using the programming language R, the course covers advanced topics such as machine learning, text mining, and social network analysis. Upon completion, students will have valuable practical analytical skills to handle large datasets and make business decisions. Credits will not be given for both BUAN 352 and BIS 452. Prerequisites: (BUAN 044 or BIS 044) and (ECO 045 or MATH 012 or MATH 231)
This course covers fundamental concepts of artificial intelligence (AI) and how it is applied to solve business problems, to increase business value, transform businesses and to gain competitive advantage. A brief technical overview will be covered. Common machine learning (ML) algorithms will be covered and students will have hands-on experience with AI tools/frameworks. Example use cases of these ML algorithms in various business functional areas will be examined. Finally, ethical challenges in the AI context will be explored. Prerequisites: (ECO 045 or MATH 012 or MATH 231) and (BUAN 044 or BIS 044 or CSE 002 or CSE 012 or CSE 007 or CSE 003)
This course explores the strategic implications of artificial intelligence (AI) in the modern business landscape. Students will learn how to integrate AI into organizational strategy to drive innovation, improve efficiency, and gain a competitive edge. Key topics include understanding AI technologies, aligning AI with business goals, ethical considerations, risk management, and the role of AI in digital transformation. Through case studies, practical applications, and hands-on projects, students will develop the skills needed to design and implement AI strategies. Prerequisites: BIS 111
Readings and research business analytics; designed for superior students who have special interest in some topic(s) not covered by the regularly scheduled courses. Written term paper(s) required. Must have preparation in business analytics acceptable to program coordinator. Repeat Status: Course may be repeated.
Special problems and issues in business analytics for which no regularly scheduled course work exists. When offered as group study, coverage varies according to interests of the instructor and students. Must have preparation in business analytics acceptable to program coordinator. Repeat Status: Course may be repeated.
Based on a student's work experience, a sponsoring faculty member shall direct readings, projects, and other assignments-including a "capstone report." It should be noted that the work experience (at least 80 hours per credit), by itself, is not the basis for academic credit. The faculty directed activity must be provided concurrent with the work. Course registration and related arrangements, including designating a sponsoring faculty member, must be made in advance of the work engagement. This course must be taken Pass/Fail. Repeat Status: Course may be repeated.
This course prepares future leaders and managers to leverage artificial intelligence (AI) as a catalyst for creative and innovative problem-solving. Students develop the mindset, skillset, and toolset required to recognize, frame, prioritize, and address complex business challenges using AI-enabled frameworks. Through structured individual and team-based processes, participants apply AI tools to analyze data, design prompt-driven solutions, and explore agent-based approaches. Live case studies across industries provide hands-on experience applying these frameworks in real-world business contexts.
This course offers a dynamic introduction to Generative AI in business, tailored for non-technical students. Using a no-code approach, students will learn Generative AI concepts, practical business applications, and prompt engineering. The course also addresses the ethical implications of AI, empowering students to use GenAI tools effectively and responsibly. This course prepares students for future careers and lays the foundation for understanding Generative AI. Prerequisites: BIS 111
This class is designed to introduce students to the processes involved in acquiring, cleaning, arranging, analyzing, and visualizing business data using the Python programming language. It will be fast-paced, but assumes only a basic familiarity with coding, and requires no specific expertise in Python to start. Students cannot receive credit for both BUAN 346 and BUAN 446.
The course covers theories and practices in predictive analytics in business. Students will have hands-on experience on analyzing business data for business intelligence and improved business decision making. Includes: key theories, concepts, and models of predictive analytics; and data mining tools to formulate and solve business problems. The course uses data analytics software and real data. Topics include prediction, forecasting, classification, clustering, data-visualization and data reduction techniques. Not available to students who have credit for BUAN 348 or BIS 456.
This course covers advanced analytic methods for understanding and solving business problems. The emphasis is on understanding and applying a wide range of modern techniques to specific decision-making situations. Using the programming language R, the course covers advanced topics such as machine learning, text mining, and social network analysis. Upon completion, students will have valuable practical analytical skills to handle large datasets and make business decisions. Credits will not be given for both BUAN 352 and BUAN 452. Prerequisites: ECO 045 or BUEC
This course covers fundamental concepts of artificial intelligence (AI) and how it is applied to solve business problems, to increase business value, transform businesses and to gain competitive advantage. A brief technical overview will be covered. Common machine learning (ML) algorithms will be covered and students will have hands-on experience with AI tools/frameworks. Example use cases of these ML algorithms in various business functional areas will be examined. Finally, ethical challenges in the AI context will be explored. Prerequisites: BUAN 446
This course explores the strategic implications of artificial intelligence (AI) in the modern business landscape. Students will learn how to integrate AI into organizational strategy to drive innovation, improve efficiency, and gain a competitive edge. Key topics include understanding AI technologies, aligning AI with business goals, ethical considerations, risk management, and the role of AI in digital transformation. Through case studies, practical applications, and hands-on projects, students will develop the skills needed to design and implement AI strategies. Prerequisites: BIS 111
