Curriculum Requirements

Master of Business Administration – Business Analytics Concentration

Academics > Degrees > Master of Business Administration, M.B.A. – Business Analytics > Curriculum

Major Requirements

Waivable Program Core (Prerequisite Courses) Credits:
ACCT 501 Accounting I 1.5
A study of accounting fundamentals. Topics include the accounting cycle, statement preparation, systems, asset valuations, accounting concepts and principles for the sole proprietorship.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
ECON 501 Principles of Economics I 1.5
A study of basic economic concepts emphasizing analysis of the aggregate economy. The fundamental concepts of national income and its determination, economic fluctuations, monetary and fiscal policies, and economic growth are covered.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
FINC 501 Finance 1.5
An overview of the financial management function in modern business, emphasizing the time value of money and financial analysis. The financial and economic environment and capital markets and securities are covered.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
MIST 501 Management Information Systems 1.5
This course provides an introduction to information technology and application software. It also introduces students to how information is used in organizations and how information technology enables improvement in decision making at all managerial levels.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
QANT 501 Business Statistics 1.5
This course introduces students to both descriptive and inferential statistics. Coverage includes applications to business and other disciplines and the use of technology as a decision support tool.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
QANT 510 Production and Operations Management 1.5
Addresses concepts and critical activities required in the manufacturing of goods and the delivery of services. Quantitative applications and the use of relevant computer software are an integral part of this course.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
    Total: 9 Credits
All students must complete this 9-credit core requirement. Courses may be waived in those instances where the undergraduate experience includes course equivalencies. Courses in this core are offered to M.B.A. students in an accelerated format.
 
Non-Waivable Program Core Credits:
ACCT 601 Managerial Accounting 3
Prerequisite: Prerequisite: ACCT 501 or a waiver

Special emphasis is placed on the collection and interpretation of data for managerial decision-making purposes. Data includes both financial accounting and cost accounting topics, such as concepts for financial statement analysis using ratios and cost control tools for internal purpose.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSI 610 Professional Development Seminar 0
This preparatory course addresses select professional skills that are requisite to success for the MBA student, and include seminars and workshops in public speaking, business writing, teamwork, critical thinking and business research.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 0-0-0
ECON 601 Managerial Economics for Decision Making 3
Prerequisite: Prerequisite: ECON 501 or a waiver.

Application of economic theory, quantitative methods and artificial intelligence (AI) to business decision making. It covers various topics including business cycles, consumer choice, product demand, marginal pricing, neoclassical and linear production theory, market structure, and choice under imperfect information. It also involves the use of empirical techniques, AI-driven model building, and advanced AI tools for business forecasting and analysis.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
FINC 601 Financial Management 3
Prerequisite: Prerequisite: FINC 501 or waiver

This course uses data and information technology resources and AI tools to emphasize the development of a comprehensive framework for the theory and practice of financial decision-making. Topics covered span a broad spectrum of financial markets and corporate financial practices including capital budgeting, risk management and mergers and acquisitions. AI is utilized to extract data and enhance financial analysis.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
MGMT 605 Organizational Behavior 3
This course provides an in-depth exploration of the key theories, and managerial practices in the field of Organizational Behavior, focusing on how individuals, group and organizational level factors influence behavior within business organization. Special attention is placed on the impact of emergent technology (e.g., AI) on organizational effectiveness.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
MIST 610 Enterprise Resource Planning Systems 1.5
Prerequisite: Prerequisite: MIST 501 or a waiver

This course provides an overview of modern Enterprise Resource Planning (ERP) systems in use today. It introduces students to how information is used in ERP systems of organizations and how information technology enables ERP systems to support decision making at all managerial levels.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
MRKT 620 Strategic Marketing and Branding 3
This course is designed to prepare the student to approach, structure, and solve complex marketing problem on strategic and tactical levels, with an extension to the other functional areas of business strategy, to align the dynamic capabilities with operations and finance. Using digital and AI tools, students will analyze the trends affecting the everchanging customers' wants and preferences, evolving market structures and competitive scenarios will reflect the present complexity of the marketing task, and the imperative of capturing market opportunities via delivery of superior customer value and the brand equity management.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
QANT 620 Multi-criteria Decision Models 1.5
Prerequisite: Prerequisite: QANT 501or a waiver

An introduction to decision sciences and the application of multi-criteria quantitative and behavioral modeling to those problems often requiring complex decisions of policy makers. Course content focuses on applications in the business environment and the use of technology as a decision support tool.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 1.5-0-1.5
QANT 630 Operations and Supply Chain Management 3
Prerequisite: Prerequisite: QANT 510 or a waiver

This course discusses a wide range of issues from how organizations successfully create and manage its operations and supply chain to how they control operations and supply chain. Using AI technologies, this course discusses key drivers and approaches organizations adopt to improve productivity and achieve competitive position. It also addresses major issues in operations and supply chain including inventory management, logistics management, facility location, total quality, material requirement planning (MRP), project management, and scheduling. The innovations and capabilities of these areas that are related to revenues and financial performance of the organizations are discussed.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
    Total: 21 Credits
The non-waivable core is an integrated educational experience where courses are delivered in modules and are highly interdisciplinary. Modules in this core may not be waived, nor can credit hours be transferred into the Division of Management as substitutes for these modules. The core must be completed, in its entirety, in the Division of Management.
 
Required Capstone Credits:
BUSI 650 Business Analytics and Decision Making 3
Prerequisite: Prerequisite: FINC 601, MRKT 620, QANT 630

This course discusses the integration of business analytics and modeling to support businesses, non-profits, and governments towards gaining insight and strengthening decision-making ability. Students will develop descriptive, predictive, and prescriptive analytics capabilities using machine learning and AI-powered tools through case studies to support decision-making in the presence of uncertainty and a large set of alternatives. The focus will be on applying these techniques to different functional areas of business, including operations, marketing, finance, and strategic planning.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
    Total: 3 Credits
Students will take the required capstone course after completing all 600-level courses.
 
Business Analytics Concentration (select four) Credits:
BUSA 701 Data Interaction and Visualization 3
This course will provide students with understanding and proficiency in data interaction and visualization. Students will use tools like Tableau and Power BI for data wrangling, visualization, and dashboard design, transforming raw data into actionable insights. Emphasizing project-based learning, the course includes AI-assisted data analysis and storytelling to solve real-world business challenges and enhance decision-making.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 710 Data Mining and Pattern Recognition for Business Analytics 3
Prerequisite: Prerequisites: MRKT 620, MIST 725 or DTSC 501

This course focuses on the theoretical foundations and practical applications of unsupervised machine learning techniques to discover hidden structures and patterns in unclassified datasets. Students will explore techniques such as clustering, association rule mining, social network analysis, and collaborative filtering, with a particular focus on their real-world applications in business. Additionally, the course integrates generative AI to demonstrate how unsupervised learning can be combined with AI to automate creative business tasks such as personalized marketing and recommendation systems. This course will integrate theoretical instruction with practical, real-world business applications, using both classical and cutting-edge AI methods.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 720 Managerial Decision Modelling 3
Prerequisite: Prerequisites: DTSC 501/MIST 725 and QANT 620

This course explores advanced forecasting, simulation, and optimization techniques to support managerial decision-making across various business functions. Students will develop predictive and simulation models using AI-powered tools to address challenges in operations, marketing, and finance. Topics include time-series forecasting methods (e.g., ARIMA, machine learning-based approaches), Monte Carlo simulations, and discrete-event modeling. The course emphasizes practical applications of AI in decision modeling, through hands-on projects using Python and @Risk, to deliver impactful business solutions.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
BUSA 730 Practical AI for Business: Deep Learning and NLP 3
Prerequisite: Prerequisites: MRKT 620, MIST 725 or DTSC 501

This course bridges the gap between AI theory and business practice, focusing on modern AI technologies like deep learning, natural language processing (NLP), and large language models (LLMs). Students will gain practical skills by building AI-powered business applications, such as Neural Networks and customer service chatbots. The course covers artificial neural networks (ANNs), NLP techniques, and cutting-edge AI tools like transformer-based models (e.g., BERT, GPT). By the end of the course, students will be equipped to deploy AI-driven solutions in real-world business environments.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
MIST 725 Fundamental Tools for Data Science 3
Prerequisite: Prerequisite: MIST 501

This course provides a comprehensive foundation in database management systems (DBMS) and data science tools, emphasizing AI-enhanced methodologies for modern business applications. Students will explore relational databases, SQL, Python programming, and business analytics, focusing on leveraging AI to optimize database design, data analytics, and visualization, through hands-on projects. This course prepares students to address real-world business challenges using innovative AI-infused data science solutions.

Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
    Total: 12 Credits
MIST 725 is cross-listed with DTSC 501: Fundamental Tools for Data Science
 
Total Required Credits = 36–45

Students with a concentration may complete the M.B.A. program in as few as 36 credits. The program consists of the waivable program core, the non-waivable program core, capstone course, and concentration courses.