Curriculum Requirements
Master of Business Administration – Business Analytics Concentration
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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 Waived for undergraduate accounting majors who have completed a baccalaureate degree within five years of acceptance into the MBA program with an average of 3.0 or better. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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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 |
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ECON 601 | Managerial Economics for Decision Making | 3 |
Prerequisite: Prerequisite: ECON 501 or a waiver. Application of economic theory and quantitative methods to business decision making. Topics: consumer choice, product demand, marginal pricing, neoclassical and linear production theory, market structure, and choice under imperfect information. Use of empirical techniques and model building for business analysis and forecasting using standard econometric software package is also addressed. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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FINC 601 | Financial Management | 3 |
Prerequisite: Prerequisite: FINC 501 or waiver Topics covered in FINC 601 span a broad spectrum of financial markets and of corporate financial practices to emphasize the development of a comprehensive framework for the theory and practice of financial decision-making. This course uses data and information technology resources to bridge the gap between abstract theories and managerial practices. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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MGMT 605 | Organizational Behavior | 3 |
The classical substance of organization and management is linked with the analysis of organizational elements and dimensions of human behavior in the work environment. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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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 |
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MRKT 620 | Strategic Marketing and Branding | 3 |
Marketing is at the core of a business enterprise. Without customers, a business cannot exist. This course prepares students to approach, structure, and solve complex marketing problems on strategic and tactical levels. Analysis of the dynamic marketplace trends affecting everchanging customer preferences, evolving market structures, and competitive scenarios will reflect the complexity of the marketing task. The course provides students an understanding of strategies and tactics for capturing market opportunities via delivery of superior customer value and brand equity management. Analysis of the trends affecting the ever changing 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 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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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 |
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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 state of the art 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 |
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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 data analytics and modeling to support businesses, non-profits, and governments towards gaining insight and strengthening decision-making ability. Students will develop predictive and prescriptive capabilities using data mining and simulation techniques through case studies and also use optimization techniques to support decision-making in the presence of uncertainty and a large set of alternatives. 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 |
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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. This course will build on the concepts of business statistics and cover data visualization practices and tools for presenting big data. Students will learn effective data wrangling and visualization with Tableau and other relevant tools. They will also learn to design and develop interactive dashboards for deeper insights into the data. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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BUSA 710 | Data Mining and Pattern Recognition for Business Analytics | 3 |
Prerequisite: Prerequisites: MRKT 620, MIST 725 or DTSC 501 This course will focus on the theoretical foundations and practical applications of unsupervised machine learning techniques, which facilitate the discovery of inherent structures and relationships within unclassified data sets. The students will learn to utilize techniques such as Clustering, Association Rule Mining, Social Network Analysis, Collaborative Filtering, and Recommendation Systems. Each subject area will be explored in depth, with a focus on algorithmic implementations and the potential applicability in various business contexts. This course will integrate theoretical instruction with practical, real-world business applications, to equip the students with a robust understanding of machine learning algorithms and the ability to leverage this knowledge in the pursuit of strategic business objectives. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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BUSA 720 | Managerial Decision Modelling | 3 |
Prerequisite: Prerequisites: DTSC 501/MIST 725 and QANT 620 This course demonstrates the role of optimization and simulation models for business applications. Linear and nonlinear programming as well as discrete event simulation techniques such as Monte Carlo will be studied and applied in a variety of business disciplines such as operations, marketing, and finance. Another focus of this course is on data analytical methods for the preparation of business forecasts. Emphasis is placed upon building time series forecasting models and evaluating their accuracy. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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BUSA 730 | Practical AI for Business: Deep Learning and NLP | 3 |
Prerequisite: Prerequisites: MRKT 620, MIST 725 or DTSC 501 This course is designed to bridge the gap between theory and practice in business analytics through the application of deep learning techniques to solve complex business problems. Students will study Artificial Neural Networks (ANNs) and their applications to regression/classification, including image recognition. They will develop a robust understanding of statistical and probabilistic Natural Language Processing (NLP), and how these contribute to business insights such as sentiment analysis and text summarization. This course will further guide students through sequential and transformer-based NLP models, supported by case studies to provide real-world context. By course conclusion, students will be equipped with the knowledge and skills to harness the power of deep learning and NLP, and their applications in driving business decisions and strategy. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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MIST 725 | Fundamental Tools for Data Science | 3 |
This course focuses on the general concepts and methodologies in database management systems (DBMS) and various fundamental tools for data science. Topics covered in this course include relational database and SQL language, Python programming language, and business analytics basics. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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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. |