- 36 (Students with business background)
- 42 (Students without business background)
With impressive concentration options ranging from accounting and finance to marketing and business analytics, our MBA gives you the flexibility to customize your curriculum by designing a unique course of study tailored to your professional background, learning style, and career aspirations.
- Learn in-demand skills, theories, and practices for managerial decision-making in a variety of business areas.
- Become confident and capable of synthesizing and analyzing vital information to make sound business decisions.
- Develop core values that help build you as an ethical manager to achieve important organizational goals.
Business background: Tuition is $43,020 ($1,195 per credit hour)
Non-business background: Tuition is $50,190 ($1,195 per credit hour)
Please see the Tuition and Financial Aid page for more information.
The MBA degree program at Fairfield University is open to students with a bachelor’s degree in any discipline, provided you have a minimum undergraduate GPA of 3.0 and a strong personal statement. No prior business experience or education is required.
GMAT Official Test Scores. We will accept the GRE in place of the GMAT. GMAT/GRE waivers are available and are based on academic and/or professional background.
Application Priority Deadline: Applications are reviewed on a rolling basis, and we will work with you right up to the start of classes for program acceptance. For priority consideration, your application and all supplemental materials must be received no later than three weeks prior to the start of each term. For any questions about application deadlines, please request more information.
It’s easy to apply. Here are the steps:
- A completed online application.
- A non-refundable $65 application fee paid by credit card. Application fee is waived for current Fairfield students and for those who attend an information session.
- A professional resume. Applicants are required to submit a current resume that includes employment and education history.
- A personal statement. Applicants describe why they want to undertake graduate studies in business.
- GMAT Official Test Scores. We will accept the GRE in place of the GMAT. GMAT/GRE waivers are available based on academic and/or professional background. To inquire about a GMAT/GRE waiver please contact Assistant Dean of Dolan Graduate Programs Leanne De Los Santos.
- Official transcripts from all colleges and universities attended demonstrating a cumulative GPA of at least 3.0. All foreign transcripts must be evaluated by an approved evaluating service.
- Two recommendation forms and letters, one of which, preferably, from a current employer or supervisor. Recommendations are completed online. At the time of application candidates must provide the email addresses and names of their two recommenders.
Faculty Spotlight
Earning an online MBA prepares you to advance your career in a rapidly growing field with diverse career opportunities. Benefit from our seasoned and interdisciplinary faculty that emphasize relevant skills centered around industry trends and employer needs that can be applied directly to your career. Fairfield’s vast alumni and industry network aims to set our students up for success beyond graduation.
Faculty Spotlight
Dr. Kim teaches in the areas of managing diversity and inclusion, conflict management, negotiation, and research methods (both quantitative and qualitative). Her research focuses on workforce diversity, cross-cultural management, and conflict management and negotiations.
Dr. Mousumi Bose Godbole earned her PhD. degree at Louisiana State University, Baton Rouge, LA in 2009. Her dissertation related to identifying a unique buying pattern named acquisitive buying. She joined Fairfield University in Fall 2009, prior to which she was at Frostburg State University, Frostburg, MD. She has 8.5 years of corporate experience in corporate sales and brand management.
Dr. McDonald teaches Principles of Finance in the MBA program. He holds a PhD in finance from the University of Tennessee and his work has been quoted by the Wall Street Journal, CNN, Nasdaq.com, Bloomberg, Reuters, and many other outlets.
Dr. Tao has a doctoral degree in information systems and helped design the curriculum for the MSBA program. He has published papers in several journals and presented research at premier academic conferences. His special interests include data analytics, data structure, process mining, and deep learning.
Expand your industry expertise and boost your resume with a certificate that can be directly applied toward your master's degree.
Graduate Business Intelligence Certificate
Designed for students without a formal analytics background.
Online courses are asynchronous to fit your busy schedule.
Learn the basics of business analysis through data visualization tools, databases, and business intelligence.
Apply skills from day one of the program to your current position.
Starts:Spring, Summer, or Fall
Schedule: Completion:$14,340 (12 credits x $1,195 per credit hour)
Graduate Business Analytics Certificate
Designed for graduates of the business intelligence certificate program and students with an extensive analytics background.
Online courses are asynchronous to fit your busy schedule.
Master the technical concepts of business analytics, predictive analytics, database systems for business analytics, and data mining.
Build competitive skills in Python, machine learning, and business forecasting.
Starts:Spring, Summer, or Fall
Schedule: Completion:$14,340 (12 credits x $1,195 per credit hour)
Degree Courses
Accounting
This course examines the basic concepts necessary to understand the information provided by financial and managerial accounting systems. The focus is on interpretation of basic information, as students learn about internal and external financial reporting. Topics include: accrual accounting; revenue and expense recognition; accounting for assets, liabilities, and equities; accumulation and assignment of costs to products and services; and budgeting. Previously AC 0400.
This course emphasizes the use of accounting information by managers for decision-making. It is designed to provide managers with the skills necessary to interpret analytical information supplied by the financial and managerial accounting systems. Financial accounting concepts based on profit, liquidity, solvency, and capital structure are used in the process of employing management accounting tools to decisions and evaluate organization performance and changes in cost, profit and investment centers. Previously AC 0500.
This course brings together technical accounting and reporting concepts and theories with a focus on the financial accounting information that is required to be filed with regulatory agencies, the most predominant being the Securities and Exchange Commission. This course aims to provide an in-depth conceptual understanding of regulatory reporting requirements coupled with an appreciation of how these regulations affect the quality of information in publicly available corporate reports. Students will enhance their ability to analyze and understand unique and complex future accounting issues and possible solutions. The course is taught seminar style with students leading the discussions of cases and research. Previously AC 0510.
This course covers concepts that are relevant in practice for both a public and private accounting and taxation setting. Drawing on and integrating complimentary law and tax topics, the course will consider issues such as: real estate used in a trade or business or held for the production of rental income, ownership of a principal residence, and indirect ownership of real-estate interests in the form of securities under federal law, including a REIT, as well as secured transactions and bankruptcy. Crosslisted with TAXN 6515.
The primary focus of this course is the study of International Financial Reporting Standards (IFRS). Particular emphasis will be placed on developing an understanding of significant differences between the current United States Generally Accepted Accounting Principles (GAAP) and IFRS standards. Students will also learn the pros and cons of U.S. GAAP and IFRS approaches for select technical accounting issues. Some other non-IFRS related topics include International Taxation, International Transfer pricing and the impact of culture on the development of accounting standards and practices throughout the world. Previously AC 0520.
This course provides students with a foundation in the Law of Commercial Transactions. The course begins with a review of the principles of common law contracts which underpins many aspects of the Uniform Commercial Code. This course entails an advanced study of several provisions of the Uniform Commercial Code (hereinafter referred to as “UCC” or “the Code”). The sections of the Code to be studied include Article 2 Sales, Article 2A Leases of Goods, Articles 3 and 4 Negotiable Instruments and Bank Deposits and Collections, and Article 9 Secured Transactions. With an emphasis on case analyses and/or problem sets, students taking the course will have the opportunity to improve their critical thinking and written and oral communication skills, particularly as they relate to the legal settings associated with the UCC. Crosslisted with TAXN 6525. Previously MG 0512.
This course examines the generally accepted accounting principles applicable to governmental entities (as issued by GASB) as well as accounting principles applicable to not-for-profit entities (as issued by FASB). The focus will be on the financial statements and reports prepared by state and local governments and financial reporting for the wide array of not-for-profit entities with an emphasis on the contrast of these entities with for-profit accounting. Previously AC 0530.
This course addresses technological topics of current interest to the accounting profession. Topics such as accounting information systems, cybersecurity, enterprise resource planning systems, and business intelligence may be discussed, but the focus of the class will be development of computer skills for extraction, data visualization, and cleaning and analysis of accounting data. Previously AC 0550.
This course covers internal audit from a broad perspective. Course topics cover three main areas: internal audit basics, risks, and metrics. During the course, students will develop critical thinking skills (particularly employing professional skepticism) and learn to effectively communicate their professional opinions. Previously AC 0555.
This course will expose students to the global profession of auditing, with a primary focus on public company auditors. Topics will vary any given semester, but may include the following: the different international organizations that set auditing standards and enforce auditing standards; the impact of culture on auditing standards and practices throughout the world; the impact of International Financial Reporting Standards on international and U.S. auditing rules; the evaluation of audit evidence; auditor independence; materiality; internal controls; computer assisted audit tools and techniques; fraud detection and forensic accounting. The course is taught seminar style, with students leading the discussions of cases and current articles. Assignments are designed to develop students’ written and oral communication skills, analytical skills, and critical thinking skills. Previously AC 0560.
This course provides students with a foundation in investigative accounting. Topics covered include identifying, investigating and documenting fraud and providing litigation support for forensic engagements. With an emphasis on case analyses and/or independent research, students taking the course will have the opportunity to improve their critical thinking and written and oral communication skills, particularly as they relate to the legal settings associated with investigative accounting. Previously AC 0565.
This course investigates ethical problems in contemporary accounting practice. The goal is to increase students’ ethical perception so they are better able to identify, consider, and ultimately act on the ethical issues they may face in their professional accounting career, regardless of specialty area (e.g., audit, tax, and corporate accounting). The course is taught seminar style, with students leading the discussions of cases and current articles. Assignments are designed to develop students’ written and oral communication skills, analytical skills, and critical thinking skills. Previously AC 0570.
The course is designed to increase and extend the knowledge of the student in financial statement information and topics introduced in undergraduate courses in intermediate and advanced financial accounting through lecture, problem solving and case analysis. A critical examination of both objective and subjective aspects of financial reporting will be undertaken with both quantitative as well as qualitative assessments of financial information emphasized. Previously AC 0580.
In this course, students will practice communicating effectively in accounting settings. Topics include considering the communication needs of accountants’ diverse audiences, adapting communications to varying purposes, and writing and speaking clearly and concisely in both preparing accounting-specific documents and in presenting accounting-focused information. Crosslisted with TAXN 6585.
This course presents recent practitioner and academic literature in various areas of accounting, including guest speakers where appropriate. Topics change semester to semester, depending upon faculty and student interests. Previously AC 0585.
This course is a designated research course. In it students will investigate, analyze, develop, and present recommendations for emerging issues, recent pronouncements of accounting rule-making bodies and/or unresolved controversies relating to contemporary financial reporting. In doing so, students will consider institutional, historical, and international perspectives. In their research, students are expected to use authoritative resources (e.g., FASB and/or IASB pronouncements). The course is taught seminar style, with students leading the discussions of cases and current articles. Assignments are designed to develop students’ written and oral communication skills, analytical skills, and critical thinking skills. Previously AC 0590.
This course builds on the in-class lessons covered during the student’s graduate studies by providing the student with the opportunity to apply their academic knowledge to a professional accounting context. As such, it is an experiential learning activity. Successful completion of the practicum will entitle students to three credits that count as a graduate-level accounting elective. Enrollment by permission of the department chair or designee. This course may not be repeated for credit. Previously AC 0591.
This course provides students with an opportunity to develop research skills while exploring a specific contemporary accounting issue with a full-time faculty member specializing in the area of the discipline. Students are expected to complete a significant research paper as the primary requirement of this course. Enrollment by permission from department chair or designee only. Previously AC 0598.
Analytics
Using spreadsheet software, this hands-on course teaches a variety of quantitative methods for analyzing data to help make decisions. Topics include: data presentation and communication, probability distributions, sampling, hypothesis testing and regression, and time series analysis. This course uses numerous case studies and examples from finance, marketing, operations, accounting, and other areas of business to illustrate the realistic use of statistical methods. Previously QA 0400, BUAN 5400.
This course is an introduction to Python, with an emphasis on general programming concepts (structure, logic, data, etc.) that apply to just about any general purpose programming language. Starting with a review of fundamental programming concepts, the course uses short lessons, quizzes, and coding challenges to cover the basics of how Python is used in a professional Business Analytics setting. The course concludes with a final project designed to demonstrate proficiency. Previously BA 0405, BUAN 5405.
This course focuses on quantitative modeling and analyzing business problems using spreadsheet software, such as Excel and its add-ins. Topics include descriptive analytics, visualizing and exploring data, predictive modeling, regression analysis, time series analysis, portfolio decisions, risk management, and simulation. Business models relevant to finance, accounting, marketing, and operations management are set up and solved, with managerial interpretations and “what if” analyses to provide further insight into real business problems and solutions. Open to MS Management students only. Previously BA 0410, BUAN 5410.
This is an introductory level graduate course focusing on spreadsheet modeling to analyze and solve business problems. Topics include descriptive analytics, data visualization, predictive modeling, time series analysis, and data mining. Contemporary analytical models utilized in finance, marketing, accounting, and management are set up and solved through case studies. Previously IS 0500, ISOM 6500.
This course provides a broad overview to the analytics profession, with a focus on data driven leadership and hands-on analytical skills. Starting with a foundation of analytical framing and statistical analysis, the course moves on to more advanced topics like data visualization and summarization, descriptive and inferential statistics, spreadsheet modeling for prediction, linear regression, risk analysis using Monte-Carlo simulation, linear and nonlinear optimization, and decision analysis. The course culminates with a group research project using curated big data datasets, as well as individual exercises in problem framing intending to be a component of an analytics capstone experience. Previously BA 0500, BUAN 6500.
In this course, we introduce Python as a language and tool for collecting, preprocessing, and visualizing data for business analytics. Since Python is one of the most popular programming languages in machine learning, its fundamental programming logic and knowledge is essential for students to apply in analytics and to succeed in the job market. Specifically, this course focuses on the data munging phase, which includes collecting, preprocessing, and visualizing data, with respect to applications in business modeling, optimization, and statistical analysis. In addition, important techniques such as web scraping and Application Programming Interface (API) usage are introduced. The course culminates with a final project in exploratory data analysis, as well as individual exercises in data munging intending to be a component of an analytics capstone experience. Previously BA 0505, BUAN 6505.
This course introduces datasets, databases, data warehouses, data management, and data visualization techniques. Starting from the relational data model and basic database fundamentals, the course offers a hands-on introduction to Structured Query Language (SQL) for defining, manipulating, accessing, and managing data, accompanied by the basics of data modeling and normalization needed to ensure data integrity, including entity relationship modeling and diagrams. Additionally, the course simultaneously offers hands-on learning with visualization and interactive dashboards in Tableau. The course concludes with a comprehensive data warehousing and visualization project that gives each student the opportunity to integrate and apply the new knowledge and skills learned from this class. Previously BA 0510, BUAN 6510.
With the rise of analytics for cutting-edge business innovation, the industry needs business leaders who can solve an organization’s most important problems by asking and answering questions using data. These business consultants need to bridge both the data analytics and business fields. This class tries to provide a “real world” consulting experience through a project-centric experiential approach, in addition to case studies of analytics consulting and business problem solving using descriptive, predictive and prescriptive analytics. When possible, class projects will be client-driven using community partners. Students work in teams using analytics to answer the client’s current and important business questions using data. The students will approach these as business analytics consultants by using effective project management to gathering requirements, using continuous client engagement to deepen understanding of the problem, suggesting ways in which to explore the question and its possible solutions through data, running different data models to approach the solution, working with clients to come up with effective analytics strategies, making business presentations based on findings, incorporating the inevitable changes that come with real world projects, and recommending strategic solutions based on their findings. Previously IS 0520.
This course introduces analytical techniques used for decision-making under uncertainty. Topics include time series and other forecasting techniques, such as Monte Carlo simulation, to assess the risk associated with managerial decisions. Specifically, we will cover data collection methods, time dependent models and analysis, advanced solver, time series techniques, exponential smoothing, moving averages, and Box-Jenkins (ARIMA) models. Application examples include financial models – stock prices, risk management – bond ratings, behavior models – customer attrition, customer likes/dislikes, buying patterns – propensity to buy, politics – identify swing voters, and sales. Previously QA 0500, BUAN 6530.
Modernly, business intelligence has become far more interactive. This course provides an advanced application and overview of the new techniques for building interactive dashboards and tools now prevalent in this profession. Additionally, with data overload happening on every level, the importance of good data storytelling has soared. Using programming languages and environments such as Tableau and R, this course introduces students to the business intelligence profession and teaches the skills necessary to develop and deploy cloud-based interactive apps to assist in data and analytical storytelling, including insights into user interface design (UI) and user experience design (UX). The course concludes with a comprehensive project. Previously BA 0540, BUAN 6540.
This course provides an advanced understanding of the practices of machine learning techniques and operations (MLOps), with a special focus on business applications. To assure practical relevance, the emphasis of this course is on the applications of techniques and tools realizing machine learning in terms of business analytics. The course is organized following the Cross-Industry Standard Process for Data Mining (CRISP-DM) and all learned techniques are applied in a couple of semester-wide projects. Python is introduced and illustrated through a series of tutorials and case studies, and Automatic Machine Learning (AutoML) is introduced as well. Students are expected to actively participate in the course deliverables through independent assignments, lab work, and group projects. The course culminates with a final project in predictive analytics, as well as individual exercises in modeling and interpretation intending to be a component of an analytics capstone experience. Previously BA 0545, BUAN 6545.
This course introduces the fundamentals of Big Data management and its implementation in the public cloud. Topics include classic theories of data architecture, dimensional database design, data pipelines, and data governance, supplemented with the latest developments in the emerging field of DataOps. The theory is grounded with hands-on experience building databases and data pipelines with the Modern Data Stack. Previously IS 0550.
Sports analytics is transforming the way teams, leagues, players, coaches, referees, and fans perceive and appreciate their favorite pastimes and games, including major team sports such as baseball, basketball, football, soccer, cricket, and rugby, more individualized sports like tennis and golf, and brand-new innovations such as e-sports. In this course, students will gain experience in framing analytical questions in sports, discover and evaluate cutting-edge research and findings in sports analytics, develop hands-on skills in using and implementing sports analytics solutions, and learn how to communicate findings to a non-analytical audience in an impactful and actionable way. This course culminates in a scholarly sports analytics research paper.
Artificial intelligence is becoming far more prevalent in the business and analytics worlds, yet many analytics professionals are excluded from participating in this new wave because they lack the strong coding foundations that are typically needed to implement this new technology from scratch. However, recent advances in AI/ML have coincided with desktop and cloud tools that can be deployed far more easily to generate new models without complicated coding requirements. This course will teach students how to discover, use, and daisy-chain such tools to solve real-world business problems in ways that would otherwise be impossible.
This course introduces students to the latest development of machine learning, namely deep learning, as well as its applications to a variety of domains. Fundamental knowledge, such as the architectures of the deep neural networks, extraction of high-level features representing unstructured data, backpropagation, and stochastic gradient descent. Additionally, students get hands-on experience building deep neural network models with Python. Topics covered in this class include model building and optimization, image classification, natural language processing, generative models, and so forth. These topics cover the foundations and the latest developments in the field of deep learning.
This course draws from current literature and practice on information systems and/or operations management. The topics change from semester to semester, depending on student and faculty interest and may include: project management, e-business, management of science with spreadsheets, e-procurement, executive information systems, and other socioeconomic factors in the use of information technology. Previously IS 0585, ISOM 6900.
This course provides an opportunity for students to complete a project or perform research under the direction of an Information Systems and Operations Management (ISOM) faculty member who has expertise in the topic being investigated. Students are expected to complete a significant project or research paper as the primary requirement of this course. Enrollment by permission of the ISOM Department Chair only. Previously IS 0598, ISOM 6990.
This capstone course for the MS Business Analytics program is to be taken in the last term before graduation. The purpose is to apply and integrate knowledge and skills learned in the program (statistics, modeling, data management, data mining, etc.) to a live data analytics project. The course is project-based, with students collaborating on their work under the guidance of faculty members. Application areas and format of the projects may vary, depending on faculty, dataset, and budget availability. However, the work should be rich enough to demonstrate mastery of business modeling and technology, with each student making a unique, demonstrable contribution to completion of the work. Previously BA 0590, BUAN 6999.
