This course teaches students to design, plan, execute, and report on a relatively large-scale AI-driven text analytics project. It includes multiple hands-on labs in both R and Python, and a semester-long research project. The textual data all around us, from social media, to websites, blogs, email archives, annual reports, meeting transcripts, newspapers, and much more, can fuel our analysis of companies, countries, organizational problems, or facilitate academic research for master’s theses or doctoral dissertations. Students explore the fundamentals of text analytics and data visualization beginning with statistical bag-of-words (BoW) approaches, moving to natural language processing (NLP) approaches including language models, word embeddings, text parsing, parts of speech (POS) tagging, and Named Entity Recognition (NER); then on to machine learning (ML) approaches, including unsupervised techniques such as topic modeling and clustering, and supervised techniques such as predictive modeling for regression and classification problems; ending with Deep Learning (DL), transformers, and large language models (LLMs) like GPT, BERT, and LLaMA that underlie Generative AI tools.

In this course students are introduced to predictive modeling methods, approaches, and tools. Students gain skills in predictive analytics to develop and use advanced predictive analytics methods; develop expertise in the use of popular tools and software for predictive analytics; learn how to develop predictive analytic questions; identify and select the most appropriate predictive analytics methods and tools, apply these methods to answer the respective questions, and present data-driven solutions.

This course provides foundations in three areas of software programming for business analytics, focusing on Python, an open source, object-oriented, general programming language with powerful capabilities like dynamic web development, data extraction from the web, and automation. First, it introduces software development and object-oriented programming. Second, it provides an overview of Python, the Python syntax, and popular Python packages for business analytics modeling. Third, the course reviews useful tools to enhance the productivity in Python, including iPython and Jupyter Notebooks.

This course introduces prominent quantitative methods of financial data analysis, with an emphasis on practical implementation. The course covers topics in four main areas including investments and asset allocation, time series analysis and forecasting, machine learning applications in finance, and event studies and causal inference methods. Students gain a theoretical understanding of the methods and hands-on experience by implementing these methods in Python.

This is an advanced course focusing on the detection and investigation of business crimes with an emphasis on the forensic accountant’s role in uncovering fraud. Topics include fraudulent financial statement analysis, fraud detection using electronic evidence, legal issues that arise during a fraud examination, a forensic accountant’s role in the litigation process as a consulting and expert witness, and other special topics.

The course covers the conceptual, practical, and managerial foundations of managing organizations in today’s digital and data-driven economy. It includes foundational aspects of information technology: digital transformation, digital competition, analytics management, cybersecurity, and emerging technologies.

Top global companies regularly fail to make insightful decisions about significant patterns and changes in their business environments and markets, even though the data related to these decisions is available. Business Intelligence (BI) connects data from multiple sources to produce meaningful information and identify patterns and trends to inform such decisions. BI encompasses the methodologies, metrics, processes, and information systems used to monitor and manage an enterprise’s business performance and support strategic decision-making. BI systems encompass a blend of technologies such as data warehousing, data mining, business analytics, predictive statistics, online analytical processing, and visual data representations (e.g., dashboards, data cubes), which when put together, provide decision makers with the most powerful business insights derived from multiple internal and external data sources. This course exposes students to the management practices, methodologies, and technologies that major corporations are applying in order to supply executives with the knowledge needed to succeed. The course includes readings, case studies, guest speakers, exposure to BI tools, and a data analytics project.

This foundation course helps students develop an understanding of the impact of entrepreneurship in business, government and society and an awareness of the mindset and skills entrepreneurs develop to build companies from ideas to inventions to successful innovations. Students examine the relationship of innovation and entrepreneurship, case histories of successful companies built by passionate entrepreneurs and the use of modern customer-centered practices used to define and develop startup companies.

For students preparing for careers in accounting; management; management consulting; financial management; and financial analysis. Introduces concepts and tools needed to understand and effectively use managerial accounting information to monitor and control costs; plan operations; and measure; monitor; and motivate performance.

This course provides a bridge between theory and practice in finance. It examines various aspects of financial economics, combining theory, empirical evidence, and application. The course focuses on theory, studying financial decision-making under uncertainty, asymmetric information, and agency problems, among other topics. It applies this theory to analyze consumer financial markets, examining the design of financial products, the role of fintech, and how firms respond to the regulatory environments in which they operate.

This course provides students with decision-making skills derived from the ability to understand, perform, and interpret complex financial calculations and models used in finance. It presents the theory and practice of finance, emphasizing computer-based financial modeling, forecasting and the use of financial software applications to analyze the impacts of financial decisions. The course covers a variety of techniques, such as sensitivity and scenario analysis, optimization methods and Monte Carlo simulation.

Financial operation of the multinational firm, including the sources of funds, foreign investment decisions, and international transactions and taxation. Also included is a study of the related aspects of the international monetary system; foreign exchange markets; measuring and managing foreign exchange risk; and international banking.

The Student Managed Investment Fund (SMIF) is a collaborative class that provides valuable, real-time experiential learning in securities analysis and portfolio management. Students learn equity valuation and portfolio management techniques and tools to demonstrate practical knowledge in research, investing, portfolio management, and the dynamics of equity markets. The course also explores AI research tools. Repeatable for credit.

The Real Estate Investment Trust Fund (REIT) is an experiential learning event that provides valuable, real-time experiential learning in REIT analysis and portfolio management. Students learn valuation and portfolio management techniques and tools to demonstrate practical and applied knowledge in research, portfolio management, and capital markets. The course also explores AI research tools.

An intensive introduction to the legal and ethical issues confronting the global business manager. Explores the legal system, legal processes, and several areas of commercial law relevant to the business manager, and also develops recognition of legal and ethical issues and their managerial implications. Examines product liability, the contract as the fundamental legal instrument of global commercial relations, agency, and the law of torts.

This course introduces students to the strategic, tactical, and operational roles of information technology (IT) and analytics in business. Students explore how successful managers leverage IT and data-driven insights to streamline operations, drive innovation, and achieve key business objectives. The course features case studies and assignments that showcase the use of IT and analytics across various business functions, including supply chain management, marketing, finance, and sustainability. Students learn how forward-thinking companies harness IT to monitor and optimize their energy consumption, reduce their carbon footprints, and enhance their overall sustainability metrics. The course also covers best practices in IT management, including developing compelling business cases for technology investments and the effective governance of IT resources. By the end of the course, students are well-equipped to understand and apply the strategic value of IT and analytics in various business contexts.

Introduces the role of the audit and assurance services in financial markets. Focuses on the ethical and legal obligations of audit professionals, practice standards, risk assessment and the evaluation of internal controls, audit evidence, levels of assurance, attestation requirements, and the impact of information technology on audit practice.

This course provides students with an understanding of data analytic thinking and terminology, and how data analytics is used in accounting-related fields. Students gain hands-on experience applying data analytics tools and techniques in financial accounting, managerial accounting, auditing, and taxation. The course utilizes Excel, Tableau, Power BI, SQL, and a variety of other apps for extracting and analyzing company financial data and presenting results of data analyses. Students gain real-world experience working with big data from real companies. Students complete this course with the skills necessary to solve accounting and business problems and develop actionable proposals for managers and clients.

In this course students learn how to conduct business analysis to document business processes and describe the functional requirements for the corresponding business application and then analyze the information requirements to support the application. The course has a strong hands-on component which prepares students for information technology (IT) consulting and business analysis practices. Students work in teams on a consulting project with an organization or consulting firm. The outcome of the consulting project is a formal specification for a business process solution to the client’s problem and the corresponding system specifications to support the solution.

This course provides foundations in three areas of software programming for business analytics, focusing on R, an open source, object-oriented software programming language. First, it introduces software development and object-oriented programming. Second, it provides an overview of R, the R syntax, R Studio (R development environment), and popular R packages and tools for business analytics modeling. Third, the course reviews useful tools to enhance productivity in R, including R Studio, R Markdown, and Shiny.

This course provides foundations in three areas of software programming for business analytics, focusing on Python, an open source, object-oriented, general programming language with powerful capabilities like dynamic web development, data extraction from the web, and automation. First, it introduces software development and object-oriented programming. Second, it provides an overview of Python, the Python syntax, and popular Python packages for business analytics modeling. Third, the course reviews useful tools to enhance the productivity in Python, including iPython and Jupyter Notebooks.

This course focuses on the business applications of advanced computational, visual, and text analytics, using both structured and unstructured data. Students gain knowledge with applied computational analytics such as prediction (classification and machine learning) and prescriptive (linear programming and data analysis). Students learn to answer business questions using visualization, discover previously unknown patterns, extract useful knowledge, and support business decision making. The course explores the application of unstructured (text) analytical applications and methods. It also introduces students to broad classes of techniques and to open source and commercial analytical tools in business problem solving.

This is an advanced course focusing on the detection and investigation of business crimes with an emphasis on the forensic accountant’s role in uncovering fraud. Topics include fraudulent financial statement analysis, fraud detection using electronic evidence, legal issues that arise during a fraud examination, a forensic accountant’s role in the litigation process as a consulting and expert witness, and other special topics.

This course focuses on the business of digital marketing. Specifically, the course covers a range of digital marketing channels, emerging technologies, and digital strategy used by marketers and organizations today. The course includes discussions and practical activities on concepts such as search engine optimization, social media marketing, paid advertising, mobile marketing, and marketing analytics (e.g., quantitative approaches used by digital marketers). Using a variety of activities and practical tools, students gain an understanding of using digital marketing to achieve marketing goals.

This course is designed to improve negotiating skills in all phases of the negotiating process through understanding prescriptive and descriptive negotiation theory as it applies to personal and professional negotiations. In-class simulations and out-of-class assignments are employed to introduce negotiation concepts in a variety of contexts, including one-on-one, multi-party, cross-cultural, third-party, and team negotiations.

This course provides an introduction to the fundamentals of marketing and business relevant to media and communications. Includes an overview of the principles of marketing, the business environment, and business strategy and an introduction to microeconomics and financial statements.

An introduction to marketing decision making in business and nonprofit organizations. Particular attention is devoted to analysis of customer needs; segmenting markets; and developing product, promotion, pricing, and distribution strategies. Students develop their business writing skills and learn through writing an integrated market analysis assignment.

Study of marketing, psychology, sociology, and cultural anthropology to determine motivations for product purchases. A multimedia approach is used to illustrate the use of behavioral science theory to create new products and promotional campaigns. Students learn to analyze consumer decisions for products or services and to determine effectiveness of information provided by government and charitable organizations.

Top global companies regularly fail to make insightful decisions about significant patterns and changes in their business environments and markets, even though the data related to these decisions is available. Business Intelligence (BI) connects data from multiple sources to produce meaningful information and identify patterns and trends to inform such decisions. BI encompasses the methodologies, metrics, processes, and information systems used to monitor and manage an enterprise’s business performance and support strategic decision-making. BI systems encompass a blend of technologies such as data warehousing, data mining, business analytics, predictive statistics, online analytical processing, and visual data representations (e.g., dashboards, data cubes), which when put together, provide decision makers with the most powerful business insights derived from multiple internal and external data sources. This course exposes students to the management practices, methodologies, and technologies that major corporations are applying in order to supply executives with the knowledge needed to succeed. The course includes readings, case studies, guest speakers, exposure to BI tools, and a data analytics project.

This foundation course helps students develop an understanding of the impact of entrepreneurship in business, government and society and an awareness of the mindset and skills entrepreneurs develop to build companies from ideas to inventions to successful innovations. Students examine the relationship of innovation and entrepreneurship, case histories of successful companies built by passionate entrepreneurs and the use of modern customer-centered practices used to define and develop startup companies.

This course provides students with decision-making skills derived from the ability to understand, perform, and interpret complex financial calculations and models used in finance. It presents the theory and practice of finance, emphasizing computer-based financial modeling, forecasting and the use of financial software applications to analyze the impacts of financial decisions. The course covers a variety of techniques, such as sensitivity and scenario analysis, optimization methods and Monte Carlo simulation.

This course introduces students to economic concepts, tools, and frameworks used by managers to evaluate the markets in which firms operate. Students complement their economic reasoning with data analysis to explore the challenges created by asymmetric information, examine the role of sustainability in regulation and international trade, and study how managers respond to U.S. and global macroeconomic events.

This course gives an overview of the fundamentals of business finance and provides students with powerful tools to understand and address financial challenges that modern businesses confront. Topics covered include financial statement analysis, time value of money, capital budgeting, valuation of bonds and stocks, risk-return trade-off, market efficiency, introduction to capital asset pricing models, and international finance. Topics are presented in a lecture/discussion format with an emphasis on practical applications, analytical thinking, and problem-solving techniques.

Investment, financing, and dividend-policy decisions of the financial manager. Case studies and problems are some of the tools used to enable the student to make and see the effects of financial decisions.

The Real Estate Investment Trust Fund (REIT) is an experiential learning event that provides valuable, real-time experiential learning in REIT analysis and portfolio management. Students learn valuation and portfolio management techniques and tools to demonstrate practical and applied knowledge in research, portfolio management, and capital markets. The course also explores AI research tools.

This course enables students to identify, critically evaluate, and respond creatively to the ethical dilemmas confronting business, whether as an employee, consumer, supplier, investor, government representative, media reporter, NGO, or other stakeholder. Through readings, lectures, case studies, and class discussions, students learn how to approach ethical questions about business decision making and behavior.

For success in life and career, students must not only have knowledge, but communicate that knowledge to others to inform, persuade, and motivate. This course uses real-world scenarios from the business world in an experiential learning format. It teaches students how to make choices in message and meaning as made by business professionals, whether they are communicating individually or in a team; and across platforms, cultures, and industries.

Students gain competency in a broad range of twenty-first century workplace technologies using hands-on learning. This includes introductions to information systems applications for planning, tracking, marketing, and control, including spreadsheet and web-based tools. The course also provides conceptual foundations in understanding technologies of hardware and software platforms of networking and security. The course includes computational thinking foundations and programming basics for business.

In this course students learn how to conduct business analysis to document business processes and describe the functional requirements for the corresponding business application and then analyze the information requirements to support the application. The course has a strong hands-on component which prepares students for information technology (IT) consulting and business analysis practices. Students work in teams on a consulting project with an organization or consulting firm. The outcome of the consulting project is a formal specification for a business process solution to the client’s problem and the corresponding system specifications to support the solution.