Business Analytics Major

ITAO 20210
Credit Hours: 3

This course introduces students to coding and computational thinking using Python, a foundational language for data analytics, machine learning, and AI-enabled business systems. The course develops students problem-solving and analytical skills through core programming fundamentals, including when and how to use different data types and structures, how to implement decision-making and iterative processes, and how to write reusable code for efficiency and scalability. Through hands-on assignments using real-world datasets relevant across business disciplines, students gain experience in collecting, analyzing, and visualizing data to support data-driven business decision-making. The course builds a foundation for more advanced coursework in analytics, AI-enabled decision making, and technology-driven
business strategy.

ITAO 20200
Credit Hours: 3

Statistical Inference in Business focuses on using data to make sound inferences about a population based on sample data, especially in business contexts. More specifically, students will learn how to make inferences using test statistics and confidence intervals in contexts of multiple groups and/or multiple variables, with multiple regression and related methods heavily emphasized. Throughout the course, issues of sampling variability, research design, causality, and the assumptions and limitations of the methods are discussed. Students will supplement their conceptual understanding of the material using statistics software.

ITAO 30160
Credit Hours: 3

The development of data insights to create a competitive advantage, optimize processes, and drive strategy is now a requirement for modern organizations. While the commercialization of data tools powered by AI has made information more accessible, it has also created an environment of “noise” that often obscures the insights necessary to create value. This course prepares students to cut through that noise by mastering the bridge between technical rigor and strategic communication. Students will develop a foundation in effectively communicating clear, actionable visual insights using Tableau — moving into advanced territory with Level of Detail (LOD) expressions and Python integration. Furthermore, the course explores the transformative role of Generative AI in the business world. Students will critically evaluate the strengths and weaknesses of AI in automating visualizations and drafting business communications, learning to leverage these tools ethically and effectively while maintaining the human-centric “last mile” of decision-making.

ITAO 40230
Credit Hours: 1.5

This course aims to help students develop advanced data analytics and AI skills to tackle real-world business challenges. Using Python, students will learn to clean, transform, and analyze large datasets to uncover meaningful patterns and translate them into business intelligence through insightful visualizations. Students will also learn the essential machine-learning techniques to forecast trends and make predictions. Additionally, students will learn how to build AI agents to automate workflows and enhance decision-making. Emphasizing practical applications, this course will equip students with extensive hands-on experience in the most popular Python libraries including NumPy, Pandas, Matplotlib, Seaborn, and more.

ITAO 30230 
Credit Hours: 1.5

This course provides a hands-on foundation in the data systems and analytical workflows that underpin modern analytics and AI applications. Students learn how structured business data is stored, managed, and queried using relational databases, with extensive practice using SQL on real-world datasets. The course also introduces data wrangling and visualization in R, focusing on transforming raw data into analysis-ready formats and communicating insights effectively. Throughout the course, students develop end-to-end data workflows spanning databases, data preparation, and analytical visualization. The course concludes with an overview of big-data concepts and unstructured data, highlighting how foundational data skills scale in contemporary data- and AI-driven organizations.

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.

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.

ITAO 40150
Credit Hours: 1.5

Data plays a crucial role in modern business, and firms rely on vast amounts of information to understand trends and anticipate key uncertainties, such as customer demand, market conditions, and operational risks. Yet the true value of data is realized only when organizations can make optimal decisions based on these insights and effectively integrate data into their business processes. This critical step, known as decision (or prescriptive) analytics, extends beyond traditional statistics and predictive analytics. In this course, students will explore simulation and optimization as essential tools for business decision-making. Through a mix of theoretical foundations and hands-on applications, students will learn how to model complex systems, obtain decisions under uncertainty, and identify the best possible actions. We will also examine a variety of real-world applications, ranging from retail and healthcare to revenue management and supply chains.

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.

• Analytics Capstone Project (ITAO 40850)
• AI and Global Business (ITAO 30320)
• AI Auditing and Governance (ITAO 40515)
• AI & Machine Learning for Urban Analytics (ITAO 40570)
• Cloud Computing (ITAO 40730)
• Cybersecurity (ITAO 30700)
• Data Wrangling (ITAO 30250)
• Designing for Human-Centered Artificial Intelligence (ITAO 50850)
• Early Bridges to Data Science (ITAO 40860)
• Emerging Technologies and Business Innovation (ITAO 30620)
• Ethics of AI and Data Analytics (ITAO 40510)
• Human-centered Analytics: Design, Measurement, and Analysis (ITAO 50860)
• Human Performance Analytics (ITAO 40530)
• Pricing Analytics (ITAO 40575)
• Society and Networks (ITAO 40550)
• Sport Analytics (ITAO 40520)

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