Master of Science in Business Analytics and AI

AI 500. Fundamentals of Artificial Intelligence. 3 Credit Hours.

This course provides a comprehensive introduction to AI, blending theoretical foundations with practical applications to equip students with essential AI knowledge and skills. Students will explore the history and evolution of AI, key technologies such as machine learning, deep learning, and natural language processing (NLP), as well as emerging advancements in generative AI. The course emphasizes hands-on experience with AI tools enabling students to build and experiment with AI-driven solutions. The course culminates in a team-based project, where students apply their learning to develop an AI application aligned with their interests. By the end, students will have a strong foundation in AI concepts, practical proficiency with AI tools, and an understanding of AI’s transformative impact across industries.
Session Cycle: Every Semester.

AI 510. AI Ethics and Society. 3 Credit Hours.

As Artificial Intelligence (AI) has increasingly been integrated across all sectors of society; it is critical to examine the challenges and ethical implications of its widespread use. This course offers a comprehensive exploration of the ethical challenges arising from the practice of AI including principles of fairness, bias, privacy, accountability, and transparency. Through critical thinking and discussion, students will analyze real-world applications, assess ethical concerns across various AI implementations, and explore how regulatory frameworks and public policies influence ethical practices. By the end of the course, students will have a strong foundation on ethical considerations in AI and be equipped to critically engage in discussions on its ethical use and societal impact.
Session Cycle: Every Semester.

AI 600. AI Applications in Business. 3 Credit Hours.

This course provides a comprehensive exploration of artificial intelligence (AI) and its strategic applications across key business domains. Students will examine how AI transforms industries, enhances decision-making, and creates competitive advantages while addressing ethical, technical, and governance challenges. The course begins by identifying AI’s opportunities, limitations, and emerging trends before diving into machine learning and generative AI applications in business. Students will explore AI’s role in marketing, finance, supply chain, and human resources through case studies, hands-on exercises, and interactive discussions. Special focus is given to human-centric AI design, AI strategy development, and governance frameworks to ensure responsible and effective implementation. A semester-long team project challenges students to apply AI concepts to real-world business problems, culminating in a final presentation.
Session Cycle: Every Semester.

FIN 501. Programming in Finance. 3 Credit Hours.

This course serves as an introduction to many aspects of Python programming, specifically as it applies to financial applications. Topics include data management, matrix operation, optimization, simulation, linear regression, portfolio management, time-series analysis, and textual analysis. Students will become familiar with and use Python to analyze and manipulate data and accomplish tasks with various financial topics.
Prerequisites: Students need to have a basic understanding of time value of money calculation, valuation of financial assets, and portfolio theory
Corequisites: MBA 524
Session Cycle: Every Spring Semester.

FIN 502. Fintech and Blockchain for Finance. 3 Credit Hours.

New technological innovations are fundamentally transforming the financial industry. This course introduces students to the different ways in which new technologies have led to material changes in business models, products, and customer user interface. The course will explore the application of AI, deep learning, and open APIs in various sectors of finance like payments, credits, trading and risk management. The course will then shift focus towards cutting-edge topics including blockchain, cryptofinance and smart contracts, mobile payments, and applications of blockchains. Along the way the course will focus on the market regulations, security compliance and changes in law needed in this rapidly changing business environment.
Prerequisites: MBA 524
Session Cycle: Every Spring Semester.

FIN 503. Fintech and Digital Innovation Fund. 3 Credit Hours.

This course will focus on two main components to provide students with a deeper understanding of Fintech, Blockchain, and the investment world. The first component will explore the impact of Fintech on different parts of the financial market through the analysis of various case studies. The case studies will cover topics such as Payment, Credit and Lending, Trading, Risk management, Insurtech. In the second component, students will also act as fintech security analysts and manage a portfolio of fintech firms funded by Bryant Alumni in the industry.
Prerequisites: FIN 502
Session Cycle: Every Summer.

FIN 691. Directed Independent Study in Finance. 3 Credit Hours.

This course is designed to allow an individual academic program to be tailored to fit the unique interests of a graduate student. At the initiation of the graduate student, the faculty member and the student will develop an academic plan that is submitted to the College of Business for final approval.

GFIN 601. Global Financial Management. 3 Credit Hours.

This course deals with the theories and principles of global management. It develops a framework for evaluating the opportunities, costs, and risks of operating in the global markets for goods, services, and financial assets. Topics include the rationale for hedging currency risk, treasury management of international transactions, managing transaction exposure to currency risk, managing operating exposure to currency risk, foreign market entry and country risk management, multinational capital budgeting, multinational capital structure and cost of capital, and corporate governance. Students will explore global financial management by analyzing case studies and preparing a country analysis report for market entry.

GFIN 691. Directed Independent Study in Global Finance. 3 Credit Hours.

This course is designed to allow an individual academic program to be tailored to fit the unique interests of a graduate student. At the initiation of the graduate student, the faculty member and the student will develop an academic plan that is submitted to the College of Business for final approval.

ISA 500. Programming Foundations for Analytics. 0 Credit Hours.

This course serves as a pre-requisite to MSDS/MABA programs for students who do not have sufficient background in programming. This course delves into the theory and pragmatics of programming with a special focus on the Python programming language. No previous experience in computer science or programming is required. You will learn basic computer programming concepts and terminologies in Python such as variables, constants, operators, expressions, conditional statements, loops, and functions. This course includes hands-on exercises to help you understand the components of Python programming while incrementally developing more significant programs, data structures and algorithms.

ISA 501. Math and Statistics Foundations for Analytics. 0 Credit Hours.

This course serves as a pre-requisite to MSDS/MABA programs for students who do not have sufficient background in math and statistics. It is for learners who have basic math skills but may not have taken algebra or pre-calculus. This course introduces the core math that data science/analytics is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Students who complete this course will master the vocabulary, notation, concepts, and algebraic rules necessary before moving on to more advanced material. Topics covered in this course include linear algebra, basic probability, statistics, and calculus.

ISA 510. Probability and Statistics for Data Analytics. 3 Credit Hours.

Probability and statistics are at the foundation of data science and artificial intelligence. The objective of this course is to provide students with an understanding of how to analyze and understand data through statistics and probability. As such, this course provides an overview of more foundational probability and statistics topics, before delving into more advanced topics through projects. Students will work with data in Python Notebooks to demonstrate their analytical skills.
Session Cycle: Every Fall Term
Yearly Cycle: Annual.

ISA 520. Data Visualization and Communication. 3 Credit Hours.

This course examines the art and science of data visualization. It teaches how to visually explore data and how to criticize, design, and implement data visualizations. It teaches the fundamentals of human perception and data visualization, exploratory data analysis and the importance of interaction in exploration, techniques for data visualization of specific data sets (networks, temporal data, geographic data, business data, etc..), and storytelling. The course will enable students to describe a visualization problem, to explore the data using visualizations, to discuss and design appropriate visualization concepts, and to implement and critically reflect on them. We will learn multiple popular data visualization tools such as Power BI, Tableau, and Python to implement our data visualization projects throughout the course.
Session Cycle: Every Fall Term
Yearly Cycle: Annual.

ISA 530. Fundamentals of AI and Machine Learning. 3 Credit Hours.

This course provides a comprehensive introduction to AI through the machine learning pipeline, covering the entire process of building, evaluating, optimizing, and deploying ML models. Core machine learning techniques in both supervised and unsupervised learning will be introduced, covering regression and classification models for labeled data, as well as clustering and dimensionality reduction methods for discovering hidden structures in unlabeled datasets. Time series forecasting will be covered to analyze sequential trends and predict future outcomes, along with reinforcement learning as a framework for decision-making in dynamic and interactive environments. With the increasing role of AI in automating and scaling ML workflows, this course will also incorporate AI tools, large language models (LLMs) and AI-assisted development platforms, to enhance the understanding, deployment, and expansion of ML models.
Session Cycle: Every Semester.

ISA 540. Data Management in the Age of AI. 3 Credit Hours.

In the era of artificial intelligence, traditional database management is evolving to support large-scale machine learning, big data processing, and AI-driven applications. This course explores the fundamentals of database management while integrating modern approaches for handling structured, semi-structured, and unstructured data in AI environments. Students will gain a solid understanding of the relational model and Structured Query Language (SQL), exploring both foundational and advanced SQL functions for various types of data analysis. In addition, students will learn how AI impacts data storage, retrieval, governance, and optimization, with a focus on NoSQL databases, vector databases, and real-time data pipelines. By the end of the course, students will be equipped to design and manage data systems that support AI applications, ensuring efficiency, compliance, and ethical considerations in AI-driven decision-making.
Session Cycle: Every Semester.

ISA 691. Directed Independent Study. 3 Credit Hours.

Students interested in exploring an idea, contributing to research, or developing a project may do so under the guidance of an affiliated faculty member in the Data Science/Business Analytics program. At the initiation of the graduate student, the faculty member and the student will develop an academic plan that is submitted to the Chair of the ISA department for approval.

ISA 692. Data Science/Business Analytics Internship. 3 Credit Hours.

ISA internships give students the opportunity for supervised employment in an area where they can apply the Data Science and/or Business Analytics skills they have studied through our curriculum. Interns work at least ten hours per week, meet periodically with a supervising faculty member, and prepare a substantive report on their work experience.
Prerequisites: ISA 510, ISA 520, ISA 530, and ISA 540.

MBA 506. Microeconomics for Business. 0 Credit Hours.

This course serves as a pre-requisite to all on-campus MBA programs for students that do not have sufficient background in the subject. The course provides an overview of microeconomics with an emphasis on understanding key concepts and principles used in business management today. The objective of the course is to teach students how to analyze an organization's performance by applying economic analysis to an array of business situations.

MBA 507. Macroeconomics for Business. 0 Credit Hours.

This course serves as a pre-requisite to all on-campus MBA programs for students that do not have sufficient background in the subject. The course provides an overview of macroeconomics with an emphasis on understanding key concepts and principles used in business management today. The objective of the course is to examine the economy in the long run (when prices are flexible) before examining the economy in the short run (when prices are sticky).

MBA 508. Statistics for Business. 0 Credit Hours.

This course serves as a pre-requisite to all on-campus MBA programs for students that do not have sufficient background in the subject. The course provides a basic background in statistics for students without prior knowledge of statistical analysis and important mathematical ratios which will be utilized throughout the MBA program.

MBA 509. Accounting for Business. 0 Credit Hours.

This course serves as a pre-requisite to all on-campus MBA programs for students that do not have sufficient background in the subject. The course provides an overview of accounting with an emphasis on understanding key concepts and principles used in business management today. The objective of the course is to teach students how to analyze an organization's performance by applying accounting principles to an array of business situations.

MBA 514. Finance for Business. 0 Credit Hours.

This course serves as a pre-requisite to all on-campus MBA programs for students that do not have sufficient background in the subject. The course provides an overview of finance with an emphasis on understanding key concepts and principles used in business management today. The objective of the course is to teach students how to analyze an organization's performance by applying finance principles to an array of business situations.

MBA 515. Management Concepts and Skills. 1 Credit Hour.

This course provides all entering MBA students with a foundation of key management perspectives and skills that will heighten student opportunity for successful program completion. During an intensive, multi-day course, MBA students will be exposed to and participate in instructional sessions addressing technology, research resources, team-building, leadership, communication skills, and case analysis exercises.

MBA 520. Managing Corporate Enterprise. 3 Credit Hours.

Successful management of a corporate enterprise begins with a coherent, well-defined strategy. This course develops the knowledge and skills necessary to analyze, formulate and implement strategy effectively. The course will address the complexity of leading a business in this era of globalization, social and technological change, and dynamic firm and industry boundaries.

MBA 521. Leading Effective Organizations. 3 Credit Hours.

This course emphasizes the importance of understanding the diverse ways that people interpret and respond to situations, emphasizing the complexity of organizational problems, especially in project-oriented, team-based environments. It discusses ways to align individual behavior with the organizations mission and objectives and encourages decision making that is consistent with established models of effective leadership and standards of ethical behavior. It equires students to create personal leadership development profiles and self-improvement plans for their professional practice to aid in the career development.

MBA 522. Reporting and Controlling Resources. 3 Credit Hours.

This course emphasizes the role of accounting in controlling the operations of an organization and the relationship between cost, profits and volume, decision making techniques using accounting data, and the use of programmed budgets as a control mechanism.

MBA 523. Managing Information Resources. 3 Credit Hours.

This course emphasizes knowledgeable and effective use of information systems, IS decision making, knowledge management, and information systems as an element of corporate strategy development.

MBA 524. Managing Financial Resources. 3 Credit Hours.

This course emphasizes the tools and techniques necessary for sound financial decision making including the time value of money, risk and return, capital budgeting, working capital management, and acquisition of long-term capital.

MBA 525. Marketing for Competitive Advantage. 3 Credit Hours.

This course emphasizes markets, innovation and opportunities, consumer characteristics affecting demand, marketing institutions, ethics and government business relations, product planning and pricing problems, distribution channels, promotion, and competitive strategy.

MBA 526. Value Formation Through Operations. 3 Credit Hours.

This course emphasizes the theories and techniques used to manage world class operations for competitive advantage including: operations strategy, process design, quality, inventory control, and project management.

MBA 528. Global Immersion Experience. 3 Credit Hours.

The Global Immersion Experience has been designed to embed the knowledge and skills needed for today’s managers to operate effectively in a globalized world. The course typically encourages students to explore a given country or region in depth and in the process become aware of the economic opportunities and pitfalls in doing business in that country/region. Students will be able to take this experience and apply it to a different country. An important aspect of GIE is a student project with an overseas firm in the destination country that builds on the first semester of academic study covering areas of strategy/leadership, supply chain management and accounting/finance. The Global Immersion Experience is required for the One Year MBA program and optional but highly recommended for the Two Year MBA. While class meetings for MBA 528 begin in the fall term, the GIE takes place during the winter term and entails travelling to a foreign country for approximately ten days.

MBA 621. Business Consulting. 3 Credit Hours.

The central idea is that consulting services, both internal and external to business organizations are useful, are in high demand, and are lucrative. The course is intended for students who wish to understand and use consulting principles and practices for competitive advantage, whether as an intrapreneur, entrepreneur, or a traditional consultant. The course introduces the taxonomy and nature of consulting, provider models and business forms such as feasibility studies, proposals, contracts, reports, and billing practices. It includes the strategic application of technology for improved productivity and performance. It helps students to understand and apply methods of thinking, process analysis, client relations, and reporting that are essential to effective consulting.

MBA 641. Long Term Career Planning. 1 Credit Hour.

MBA 645. MBA Business Practicum. 3 Credit Hours.

Students will work with a corporation or non-profit organization to develop and implement solutions to business problems or plans to exploit business opportunities. Teams will work closely with company executives to develop a project that adds value to the firm and provides students with hands-on experience working with a company.

MBA 651. Mastering Strategic Analysis. 3 Credit Hours.

This MBA Capstone course emphasizes managerial decision-making that involves all aspects of a firm and crosses all functional lines, focusing on the integration of acquired knowledge for strategy development.

MBA 691. Directed Independent Study in Business. 3 Credit Hours.

This course is designed to allow an individual academic program to be tailored to fit the unique interests of a graduate student. At the initiation of the graduate student, the faculty member and the student will develop an academic plan that is submitted to the College of Business for final approval.

MSBA 515. Preparing for MSBA and AI Success. 1 Credit Hour.

This course is designed to provide entering MSBA and AI students with the skills necessary to be successful in a graduate business analytics program. Spanning two full days, it focuses on foundational knowledge in statistics, programming, data visualization, and communication. Moreover, the course offers insights into program expectations and introduces students to the available computing resources.

MSBA 610. Time Series Analysis and Optimization for Business Decisions. 3 Credit Hours.

In this course, students will become familiar with modern data analytics methods to understand, analyze, and suggest solutions to business problems. Specifically, this course will provide an overview of time series, forecasting, and optimization techniques. This course will introduce students to a general class of models that can be used to represent time series data and investigate common time series modeling and forecasting methodologies. In addition, students will be introduced to optimization techniques including linear and non-linear programming methods. The course will equip students with a sound foundation in model building for a variety of business decision-making applications. In particular, this hands-on-the-data course offers an introduction to quantitative methods and prepares students to turn real-world problems into mathematical models. The application areas are diverse and originate from problems in finance, government, marketing, transportation, management, accounting, human resources, and healthcare.
Session Cycle: Summer Term 1
Yearly Cycle: Yearly.

MSBA 620. Marketing Analytics. 3 Credit Hours.

This course will provide students with an introduction to marketing analytics. Students will study various tools for generating marketing insights from empirical data in such areas as segmentation, targeting and positioning, satisfaction management, customer lifetime analysis, customer choice, and product and price decisions using conjoint analysis. Students will apply the tools such as Excel, R, and Tableau studied to actual marketing business situations. Students will have hands-on experience of data analysis.
Pre/Corequisites: ISA 510
Session Cycle: Spring
Yearly Cycle: Yearly.

MSBA 630. Business Strategy and Analysis. 3 Credit Hours.

This course explores the role of analytics and business intelligence in an organization’s evaluation of the strategic environment, the application of strategic frameworks to formulate a strategy, and the implementation of that strategy. The course will give students a thorough understanding of the interplay between analytics and strategic considerations in an organization. More specifically, students will learn the practical application of analytics to formulate an organization's strategy and reversely the influence of the organization's strategy to the nature of the analytics within the organization.

MSBA 640. Business Analytics and AI Capstone. 3 Credit Hours.

The Capstone course provides students with an opportunity to apply their acquired knowledge and skills to real-world problems involving large datasets. The course centers on a project based on data from a Bryant University business partner, who will provide real data and define a typical decision problem solvable through data analysis. Students will present their findings and recommendations to the class and, when appropriate, to the client. They are expected to create and confidently deliver a professional presentation of their work. The project will involve developing multiple AI and/or predictive models using Python, applying predictive modeling techniques learned in prior courses. The class will review these techniques before beginning model development.
Prerequisites: ISA 530
Session Cycle: Summer Term 2
Yearly Cycle: Yearly.

MSBA 691. Directed Independent Study. 3 Credit Hours.

This course is designed to allow an individual academic program to be tailored to fit the unique interests of a graduate student. At the initiation of the graduate student, the faculty member and the student will develop an academic plan that is submitted to the College of Business for final approval.