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Online M.S. in Accounting Courses

Curriculum Details

36 total credits required

The University of New Haven’s online Master of Science in Accounting program features concentrations in forensic accounting and artificial intelligence analytics (STEM). Both concentration options provide specialized knowledge in sought-after skill areas.

Our online accounting courses are taught by a faculty of experienced accounting professionals who are dedicated to your success. The hands-on curriculum is delivered in a flexible, accelerated format designed for working adults with busy schedules.

This program consists of 36 credit hours of advanced accounting coursework, combining a core of essential skill development with in-depth training in your chosen concentration. Depending on your previous education, some courses can be waived or substituted to accelerate your degree. Online accounting courses are seven weeks in duration and most students complete the program in 12 to 18 months.

Core Courses

An examination of financial accounting reports, standards, practices, and procedres from a user’s perspective, emphasizing the understanding and use of accounting reports rather than their preparation. Basic terms, concepts, reports, and underlying theories are covered. A review of the effects of choosing certain accounting methods, policies, and procedures is intended to enhance the manager’s comprehension of financial statement presentation.
Accounting analysis for the managerial functions of planning, controlling, and evaluating the performance of the business firm.

Prerequisite: ACCT 6619 or ACCT 6620. A selective examination of corporate financial accounting topics including revenue recognition and income determination, structure of financial position and cash flow statements, issues related to current assets, long term assets, liabilities and shareholders; equities. This course will be substituted with an accounting elective if at least two intermediate accounting courses are taken in an undergraduate accounting program in the U.S. or Canada.

Prerequisite: ACCT 6630. This course covers advanced topics in financial reporting including: accounting for partnerships, state and local governmental units, not-for-profit organizations, and accounting for mergers and consolidations.

Prerequisite: ACCT 6630 or six hours of intermediate accounting. Theoretical aspects of accepted accounting principles and their significance as a frame of reference for the valuation of accounting practices. Major focus on the role of regulatory agencies and professional accounting organizations with regard to their influences on accounting theory and practice.

An analysis of the contemporary problems surrounding the attest function performed by the professional independent auditor.

Prerequisite: ACCT 6621. Techniques in analyzing financial statements by creditors and equity investors for the short and long term. Review of accounting principles as reflected in the financial statements.
A planned program of individual study under the supervision of a member of the faculty.

Forensics Concentration Courses

Prerequisite: ACCT 6630 or equivalent. An overview and examination of investigative auditing techniques, criminology, and courtroom procedures for the forensic accountant. The course covers both litigation support and investigative accounting, examining the practical aspects of these two areas, as well as many of the newer technological areas. The course also examines corporate compliance programs to comply with Sarbanes-Oxley and the Foreign Corrupt Practices Act. 3 credits.

Prerequisite: ACCT 6630 or equivalent. This course examines the basis and framework of business valuation theory and applies those theories in practice. Discussion will center upon the elements of valuation from financial and operational analysis through the methods found in the three approaches to valuation: asset, income, and market. Highlights include the development of discount/capitalization rates and the application of appropriate adjustments (i.e., premiums and discounts) to the calculated value. This course also addresses a range of matters including fraud, economic damages, professional standard of care, valuation, and others. This course is designed to provide an introduction to financial forensics. It will provide an overview of the types of engagements in which financial experts are called upon to render financial, analytic, investigative, and expert testimony. 3 credits.

Prerequisite: ACCT 6630. An examination of concepts and skills of fraud investigation and forensic accounting. Course coverage includes an overview of the fraud problem; prevention and detection of fraud and the use of technology to detect fraud; elements of fraud investigation, interview techniques, fraud types; employee, management, investment, vendor, and customer schemes; laws governing the prosecution of fraud cases. 3 credits.
This course examines the role of forensic accountants in litigation from pre-lawsuit assessments through trial including investigation, evaluation, and discovery of accounting and financial information, expert reports, and presentation of evidence. Professional standards for forensic accountants and legal rules governing ethical forensic accounting practices and testimony of experts as well as acquisition, retention, and use of accounting information will also be studied. The course will include a combination of theory and practice. 3 credits.
Prerequisite: LSTD 6640. This course will provide an overview of the different laws relevant to litigation support and forensic accounting. With a focus on litigation support for private disputes, the course will study legal issues concerning infringement of intellectual property rights, employment law matters, privacy in electronic communications, securities regulation, Sarbanes Oxley Act requirements, international issues, and matrimonial and estate disputes. 3 credits.
Prerequisite: LSTD 6640. This course surveys the law governing various types of fraud, including elements of civil and criminal fraud, regulation of fraud, and methods for investigation and prevention in a legal context. Students will study types of fraud, documents, sources of evidence, and analysis of internal and external fraud schemes with an emphasis on the skills needed to identify, investigate, and prevent fraud. 3 credits.

Artificial Intelligence (AI)/Analytics (STEM) Concentration Courses

This course reviews statistical concepts and methods with emphasis on data analytics and visualizations. Topics to be covered include descriptive statistics, plots and graphs for discrete and continuous data, statistical inference, regression, and selected non-parametrics including chi-square. In addition, power pivot and other Excel analytical tools will be covered. Students will obtain a solid introduction to R as a functional programming language and will be able to use Excel and R to effectively compute statistical and graphical procedures. 3 credits.
Prerequisite: BANL 6100. This course focuses on the art of communicating ideas imbedded in data through visual means to include spatial representations. Students are introduced to industry-standard graphic and data design techniques used to create understandable visualizations in order to communicate effectively with a particular audience. Techniques in organizing and articulating data are developed using real world examples. The course materials, assignments and project will all be prepared using the R programming language.
Prerequisite: BANL 6100. The course consists of applied training in foundational topics for supervised learning such as Linear Regression, Nearest Neighbors, and Neural Networks. It first builds a sound understanding of data preparation, exploration, and reduction methods. It covers both prediction as well as classification processes. The emphasis is on understanding the application of a wide range of modern machine learning techniques to specific decision-making situations across business domains, rather than on mastering the mathematical and computational foundations of the techniques. The R programming language will be used for instruction.
Prerequisite: BANL 6100. The course consists of applied training in foundational topics for unsupervised learning such as Association Rules, Cluster Analysis, and Text Mining. It first builds a sound understanding of data preparation, exploration, and reduction methods. It covers both prediction as well as classification processes. The emphasis is on understanding the application of a wide range of modern machine learning techniques to specific decision-making situations across business domains. The R programming language will be used for instruction.
Prerequisite: BANL 6100. This course will introduce students to foundations of relational database design and management with a focus on business domains and business analytics applications. Topics include database design principles (to include connecting and updating), entity-relationship diagrams, constructing queries in SQL, and analyzing databases – critical skills for data analysts. The course materials, assignments, and project will all be prepared using the R programming language.

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