This course introduces basic skills necessary for business analytics such as data analysis and preparation, probability and statistical modeling, data-driven decision making, and persuasion/storytelling with data. Spreadsheets are used as the platform for conducting analyses, performing statistical calculations, and presenting results. Previously DATA 2101.

This is a required lab component of DATA 1101 with a focus on Microsoft Excel. The lab is designed to improve students' spreadsheet skills, which is vital in today's job market. The lab also prepares students to pass a certification exam that is offered in a secure, proctored format during the course. A passing grade in this lab corresponds to successful completion of the certification exam.

This course focuses on the practical application of no-code artificial intelligence (AI) tools to solve complex business problems. These tools require no programming, instead emphasizing skills such as prompt engineering and the strategic use of large language models like ChatGPT. Through hands-on weekly projects and a comprehensive final project, students will learn to navigate and apply desktop and cloud-based generative AI tools in application areas including text, images, audio, video, code, and tabular data, preparing them to innovate and lead in the new age of AI.

This course introduces basic skills necessary for business analytics such as data analysis and preparation, probability and statistical modeling, data-driven decision making, and persuasion/storytelling with data. Spreadsheets are used as the platform for conducting analyses, performing statistical calculations, and presenting results. Previously BUAN 2101.

This course introduces students to project management and its role in business operations, with applications in such functional areas as accounting, finance, information systems, management, and marketing. Topics include the linkage between projects and organizational strategy, project planning and scheduling, project development and implementation, applying best practices and tools, evaluation methodologies and control techniques, and critical success factors. Special attention is given to showing how concepts and models presented in lectures and readings apply to real-world projects. Previously ISOM 2140.

Students may take up to two semesters of a department-approved internship. Students must be matriculated in the Dolan School of Business and have a GPA of 2.5 or higher. Previously BUAN 2980.

This course focuses on quantitative modeling and analyzing business problems using spreadsheet software such as Excel, and data visualization software such as Tableau. Topics include descriptive analytics, visualizing and exploring data, predictive modeling, regression analysis, time series analysis, portfolio decisions, risk management, and simulation. Business models relevant to finance, accounting, marketing, and operations management are set up and solved, with managerial interpretations and "what if" analyses to provide further insight into real business problems and solutions. Previously BUAN 3210.

This course introduces students to business analytics using Python. Students should gain a fundamental understanding of how analytics can be done using Python. Business problems will be used for assignments and projects. Technical topics include reading/writing to files, data types, variables, simple control logic, loops, strings, lists, dictionaries, functions, and structure. Previously BUAN 3235.

This course covers fundamental database concepts, such as tables and queries, using Microsoft Access. Students then gain hands-on knowledge with the industry-standard database language, Structured Query Language (SQL). A semester-wide project helps students bring together learned concepts. Students also learn how to use a popular data analytics software, Alteryx.

Virtually every sport has been improved in recent years with the introduction and widespread acceptance of analytical methods. Analytics help leagues, teams, referees, coaches, athletes, agents, and fans appreciate their favorite sports on a higher level. In this course, students will gain a broad perspective on the methods, findings, impact, and controversies within sports analytics across a variety of sports and e-sports, learn how to analytically evaluate and compare differing perspectives, and practice communicating findings to a non-analytical audience in an impactful and actionable way.

Students may take up to two semesters of a department-approved internship. Students must be matriculated in the Dolan School of Business and have a GPA of 2.5 or higher. Previously ISOM 3980, BUAN 3980.

This course aims to introduce students to Python programming, leveraging generative AI to enhance learning and practical application. The course will cover fundamental programming concepts, data structures, and logical thinking, while also focusing on the use of AI models to assist in coding and evaluating AI-generated responses. Ultimately, this course aims to prepare students for their future careers by equipping them with valuable technical skills and AI literacy.  

Business Intelligence (BI) is an umbrella concept covering the processes and methods of collecting, storing, and analyzing data generated from business operations or activities to make informed business decisions. Disparate industries, such as retail, healthcare, and education, have adopted BI for various decision support purposes. Since data in today’s business environments is vast in volume and grows at a fast pace, utilizing computerized technologies helps managers make fact-based decisions to support business operations. This course provides an introduction to the use of business intelligence and data visualization in organizations, with emphasis on how data is gathered, stored, analyzed, and used. Topics covered include business intelligence, data warehousing, data visualization, and business reporting. Previously BUAN 4310.

This course provides students with a practical understanding of data mining, applications, techniques, and tools, with a specific focus on business analytics. The pillars of the data mining process (data collection/extraction and mining) are demonstrated with real world examples. Applications of these techniques and tools to different areas are covered. A semester-wide team project provides students with hands-on experience to bring together data mining concepts learned. Previously BUAN 4315.

Students pursue topics of special interest through independent study, research, and/or completion of a business analytics project under the supervision of a full-time faculty member. The Department Chair and Dean must approve the work. The student and the faculty project advisor must submit an application to the Registrar before registering for the course. If any work is expected to occur at any time other than the semester registered, students must obtain the approval of the faculty project advisor and the Department Chair prior to commencing of any work. Normally, students should have completed at least two advanced business analytics courses before taking the independent study. Previously ISOM 4990.

This course is the capstone for the business analytics major. Students collaborate on different types of analytical projects of varying scope and complexity. Each student acquires and applies specialized technical and managerial expertise as required for completing the projects. The capstone projects will be real-world, client-oriented, and faculty-guided applications. Supplementary instruction in analytical project design, development, and evaluation is provided on an as-needed basis within the context of the project work. Previously BUAN 4999.

This course helps students understand the role of information systems in the contemporary business environment. It introduces them to the use of information systems concepts and techniques in solving a wide range of business problems. Working in small teams, students develop, analyze, and present solutions to a business problem using information technology. Previously IS 0100.

This course provides the primary exposure to service and manufacturing operations management within the business core curriculum. Topics include process modeling, quality management and control, decision analysis, capacity planning, supply chain management, and project planning and control. Special attention is given to showing how concepts and models presented in lectures and readings apply to real-world business situations. Examples of international operations are studied, and ethical issues are explored within the context of decisions such as where to locate facilities. Previously OM 0101.

Students learn the theory and practice of front-end web design. Theoretical content will primarily focus on website design, with a heavy emphasis on developing sites that conform to standards and are responsive to the needs of practical applications and mobile devices. Hands-on work will help develop technical skills, such as HTML, CSS, XML, and other web client technologies. Students will learn to use a professional-quality toolset and to follow generally accepted best practices. The course includes weekly web-programming assignments and a semester project. Previously IS 0135.

Common wisdom dictates, "You can’t get a job without experience, and you can’t get experience without a job." While having experience helps tremendously in obtaining a job, one can get experience without a job, and that is the goal of this course. In this course, students will attempt to work on a live project with real clients, preferably a client with social goals, i.e., they aim to make a positive impact on the world by helping the less privileged, either directly or indirectly. Working on a real, live project, and interacting with real clients will teach students several of the skills they need as a systems analyst. As the course progresses, students will learn about requirements elicitation, and several diagramming techniques to analyze the system that will be built. Previously IS 0240.

This course examines e-business applications such as knowledge management, enterprise resource planning (ERP), customer relationship management (CRM), and mobile applications in inter-organizational, national, and global business environments. Students explore new e-business applications, the economics of e-business, value chains and value networks, related legal and ethical issues, information privacy and security, disaster planning and recovery, and the impact of emerging e-business and mobile applications. The course includes a brief introduction to technical architecture, technology, solutions, and financing required for effective e-business applications. Students investigate emerging opportunities, challenges, and trends through interactive team exercises, case studies, and individual research projects and presentations. Previously IS 0310.

Students work in collaborating teams to design and build a networked information system. Emphasis is placed on development as an ongoing iterative and incremental process. Standard CASE tools, design patterns, and business practices are used to ensure proper communication and integration across development teams. Previously IS 0320.