AI Analytics in Business Minor

Course Number: ITAO 30100
Credit Hours: 3

Business Analytics allows us to make sense of what we see in the real world by using data and a systematic approach to solve real problems and make business decisions. This course provides the fundamental concepts and methods needed to understand the emerging role of business analytics in organizations. You will learn how to properly plan an analytics strategy, collect data, analyze the data and report findings through visualizations and storytelling. Having a strong understanding of concepts in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success in the remainder of the Business Analytics major and beyond.

Course Number: ITAO 30170
Credit Hours: 3

This course equips students with practical skills for working with generative AI in modern academic and business settings. Students learn how large language models work and how to use them thoughtfully for data analysis, modeling, research, and communication. The course emphasizes using AI to improve insight and clarity while maintaining responsibility and independent judgment. It is designed for students who want to be prepared, not surprised, by how AI is reshaping business work.

Department: Accountancy
Course Number: ACCT 30280
Credit Hours: 3

This course applies data analytics to settings within accounting, using statistics as the primary method and Microsoft Excel as the primary tool along with other add-ins and programs. The aim of the course is to enhance a student’s ability to think systematically about data, structure it into a usable and interpretable form, create decision models, and weigh probability, risk, trade offs, and the limitations of data.

Department: Accountancy
Course Number: ACCT 40280 
Credit Hours: 3

This course will advance your skills in the analytical tools most commonly used in current accounting and financial consulting practices, and will include applications in regulatory compliance, financial management and reporting, investment analysis, forecasting, valuation and simulations, operations management, forensics, and financial analysis. You will use advanced Excel techniques in forensic and financial analytics, as well as extraction, transformation, visualization, regression, natural language processing, and data management tools in Tableau, R, Alteryx, and Python. These analytical skills will allow you to identify areas where you can add value by identifying anomalies with respect to fraud, internal controls, or key financial, audit risk, and/or tax positions and the associated risks or opportunities for clients and stakeholders. Moreover, you will have confidence in the topics incorporated into the new CPA Evolution 2024 for applied technology, including: relational databases, normalization of data, structured and unstructured data, data extraction and transformation, forecasting to model financial results, cybersecurity, sensitivity analysis, and predictive analytics.

Course Number: ACCT 40850
Credit Hours: 1.5

Course Number: ITAO 30220
Credit Hours: 3

The unprecedented availability of data and information now allows companies to rely on facts rather than intuition to drive their business decisions. Giant online retailers like Amazon.com investigate customers’ browsing histories to recommend products that may be of interest to customers. Banks study the payment patterns of old customers to predict the likelihood that new borrowers will default. Wireless providers analyze usage data to predict customer turnover. Firms can make better strategic and tactical decisions and gain competitive advantages by leveraging the tremendous amount of data now available on the table. We’ll study the tools and techniques these companies and others use to make better and faster decisions, and we’ll learn about how methods such as data mining can be used to extract knowledge from data.

Course Number: ITAO 40515
Credit Hours: 3

As artificial intelligence (AI) grows increasingly pervasive in society, it is essential that we develop an understanding of how AI systems work. A vital part of this understanding is a careful consideration of various risks (e.g., the presence of bias, a lack of transparency, regulatory compliance) when AI systems are designed and deployed in real-world settings. To understand and address these concerns, this course introduces students to the fundamentals of AI auditing ? the practice of evaluating and improving the ethics of AI systems. Through a combination of interactive discussions and semi-technical lab sessions, students will develop an auditing “toolkit.” This toolkit includes both theoretical and technical concepts, especially relevant for the increasingly interdisciplinary teams of the modern workforce. Students will work on group case assignments as “audit committees” that reflect the needs of a variety of stakeholders (e.g., developers, managers, investors, users). Groups will identify and discuss potential concerns or risks associated with AI systems as well as develop recommendations to address them. Overall, the course aims to provide an interdisciplinary and hands-on introduction to AI auditing, allowing students to gain insights into the opportunities and challenges associated with the design and deployment of AI systems that minimize societal risk and increase their effectiveness.

Course Number: ITAO 40420
Credit Hours: 1.5

Machine learning is the science of getting technology systems to act without following prescriptive software. Most AI is unknowingly used daily by humans in their cars, homes, companies and experience it in the infrastructure of our nation. Most think we are in the midst of a new industrial revolution that is driven by AI software accompanied by sensors and big data that feed the software what it needs to act. This course will teach machine learning techniques and the application of those techniques. The course will cover supervised learning, unsupervised learning, best practices and AI safety or the ethics of AI. The course will examine real life examples such as robotic control, text understanding, medical informatics, and many other areas being impacted by machine learning.

Course Number: ITAO 40250
Credit Hours: 1.5

Approximately 80% of the world’s data is unstructured, that is data that does not conform to relational database principles. It is growing at fifteen times the rate of structured data. Unstructured data includes corporate e-mails, financial filings, customer feedback, blogs, online reviews, instant messages, tweets, pictures, videos, and graphs among others. Extraction of insights from unstructured data is increasingly viewed as a high-valued opportunity but is still a nascent area within many companies and other organizations. Analytic techniques are increasingly important for understanding what can be learned from unstructured data sets and demand is strong for unstructured data analytical skills.

This course introduces students to the process of performing high-valued analytics with unstructured and semi-structured data to support business decisions. Students will identify relevant data sources (big and small), learn how to use contemporary technologies such as the Hadoop ecosystem to store and process the data, implement advanced processing and analytical techniques, and develop predictive models. The course will introduce and use concepts in machine learning, natural language processing and information retrieval to solve real-world problems.

Course Number: ITAO 40510
Credit Hours: 1.5

Data-informed decision making has created new opportunities, but also expands the set of possible risks to organizations. One of these risks comes from grappling with the “should we?” question with regard to data and analytics, and associated concerns with identity, privacy, ownership, and reputation. In this course, we will explore several frameworks to address the issues related to the proper roles of public law, government regulation, professional codes, organizational approaches, and individual ethics in performing and managing analytics activities. The course will cover applicable theory and guidelines, and also make use of case studies. Upon completion, the student should be comfortable adapting one of these ethical frameworks for use in alignment with their organizational mission.

Course Number: ITAO 30660
Credit Hours: 3

Whether you become a high-profile real estate developer, an investment banker, or an entrepreneur, in any career you’ll need some project management skills to get your job done. Everyone tries to get projects finished on time and under budget, but many critical business projects fail anyway. We’ll learn the steps associated with successful project management, examine some optimization techniques, learn how to use the software tools that enhance productivity, and discuss how to avoid the implementation pitfalls that cause good people doing good projects to fail.

Course Number: ITAO 40520
Credit Hours: 1.5

Many industries are being created and transformed by using the techniques of business analytics. With the goal of studying these techniques in some depth, this course focuses on one such industry: sports. This industry has clearly benefited from the application of a wide variety of analytics techniques and has the advantage of being widely and closely followed, with large amounts of easily-accessible real-world data. Topics for study in this course include how to evaluate players, rate teams, schedule leagues, and enhance coaching strategies. Assignments involve the hands-on use of a variety of techniques and tools, which are useful in most industries. Techniques and tools include data manipulation, probability, statistics, optimization, spreadsheets, and a powerful statistics package. A basic knowledge of Excel, statistics, and sports (in particular, baseball, basketball, and football) is assumed. (You do not have to be a sports fanatic.)

Course Number: ITAO 40550
Credit Hours: 1.5

Broadly speaking, social networks are the patterns of relationships between actors. As actors in these systems are not independent, each actor influences the behaviors of others in the network. Our connections to others can determine a great many aspects of our lives, including whether or not we are employed, our happiness, and even our weight status. In this course, we will cover a variety of substantive areas in which networks can influence social life, including political behavior, innovation, inequality, power, and antagonism. Students in this course will explore the theory of network structure and function, understand how networks affect our lives and organizations, and will learn basic techniques for analyzing social network data. At the end of this class, students will have the knowledge and tools required to explore their own interests within the application of social networks.

Course Number: ITAO 50840
Credit Hours: 3

Designing effective machine learning solutions has become an important topic in industry and academic research. In particular, human-centered AI – the design, development, and application of advanced machine learning and user modeling methods to human generated content including structured, text, image, and sensor-based data – has garnered considerable attention due to its immense potential to generate business value and improve the human condition. However, this value proposition also comes with a bevy of AI governance concerns attributable to the use of increasingly complex black box models. Using a combination of academic readings and real- world examples, this seminar-style course will discuss the state-of-the-art for human-centered AI. Students will be introduced to design frameworks and best practices for developing novel machine learning artifacts and measuring their utility with respect to model performance, monetary value, and humanistic outcomes.

Course Number: FIN 40260
Credit Hours: 3

This course is intended to provide Finance majors with a working knowledge of the open source programming language Python. The course will teach the essential aspects of coding in Python and then apply the tool to financial applications involving analytics, large datasets, and unstructured data. The objective of the course is to provide students with a better understanding of how computers can be used to solve business problems. Students will be required to bring their own computer to class.

Department: Marketing
Course Number: MARK 30130
Credit Hours: 3

Marketing is an increasingly analytical profession driven by the availability of data and analytical techniques to improve decision making. This undergraduate course will introduce decision models that rely on financial data, other marketing metrics including web based key performance indicators, as well as statistical analyses. This course seeks to integrate the various analytical techniques taught in the business school within a marketing context. This course is appropriate for individuals considering careers in brand management, product management, retail management, marketing research, or consulting.

Department: Marketing
Course Number: MARK 40150
Credit Hours: 3

This course will teach you how marketing managers make decisions about pricing and distribution, using data. We begin with understanding pricing and promoting to an individual customer, and use this foundation as we move to more aggregate decisions, such as setting regular and promoted prices at the product level and managing category pricing. A key part of the class is understanding the limitations of different types of data and how better planning can both simplify the analysis and increase your confidence in the findings. This class is designed to be very practical and hands-on. A working knowledge of statistics (e.g., t-test and regression analysis) is required and you will learn R for the analysis.

Department: Management & Organization
Course Number: MGTO 30633
Credit Hours: 3

Anita Roddick built the Body Shop on the stories behind her products. Walt Disney told stories that created an immersive experience in magical worlds. Richard Bronson never shied away from telling an unpolished story, knowing that flaws make a story memorable. Among the greatest storytellers of all time, these three understood the power of storytelling to inspire others, drive decision-making, and ignite action, particularly when combined with data and sound logic. This course teaches students the art of clear, effective, and engaging data presentation using storytelling techniques. Delivered in a hands-on, workshop-style format, students build a data story from start to finish focusing on context, visual design, strategic messaging, and persuasive delivery.