In this course students will learn to prepare and interpret the three major components of the corporate annual report: the Balance Sheet, the Income Statement, and the Statement of Cash Flows. The underlying accounting model that produces these statements will be critically reviewed; both its strengths and limitations will be evaluated. Additionally the role of popular ratios in forecasting firm profitability, risk, and liquidity are considered. Student will gain this knowledge through homework assignments, discussion questions, and an integrative case analysis.

In this course students will learn to prepare and interpret the three major components of the corporate annual report: the Balance Sheet, the Income Statement, and the Statement of Cash Flows. The underlying accounting model that produces these statements will be critically reviewed; both its strengths and limitations will be evaluated. Additionally the role of popular ratios in forecasting firm profitability, risk, and liquidity are considered. Student will gain this knowledge through homework assignments, discussion questions, and an integrative case analysis.

This course builds upon the content covered in Exploring Data Analytics for Accounting Professionals, by continuing to develop the skill set and approaches needed to be an analytically-minded accounting professional. Students will learn how to assess and communicate business problems, to evaluate and analyze data and to develop and effectively present data-driven recommendations.

This course provides an introduction to programming with a focus on business and analytics applications. The curriculum supports the development of skills in data extraction and manipulation as well as automating data analysis tasks. Students will become adept in the use of important libraries and will be able to use trusted open-source resources to support continued development of programming skills. No prior programming experience expected.

This course provides an introduction to programming with a focus on business and analytics applications. The curriculum supports the development of skills in data extraction and manipulation as well as automating data analysis tasks. Students will become adept in the use of important libraries and will be able to use trusted open-source resources to support continued development of programming skills. No prior programming experience expected.

This course provides an introduction to programming with a focus on business and analytics applications. The curriculum supports the development of skills in data extraction and manipulation as well as automating data analysis tasks. Students will become adept in the use of important libraries and will be able to use trusted open-source resources to support continued development of programming skills. No prior programming experience expected.

This course helps you develop a basic understanding of auditing theory and practice by introducing you to the objectives of auditing and the decision-making process used by auditors to accomplish those objectives. The basic financial statement audit process is discussed including the concepts of evidence, materiality, and risk.

Federal income tax law; emphasis on individual and business topics. Topics include determination of income, exemptions, deductions, credits and the taxation of business entities. Problems and tax cases involving the use of tax forms.

Cost management information is needed to plan, direct, and control business operations. Topics include determining costs of products and services with various costing systems, cost-volume profit analysis, budgeting, and variance analysis, with a focus on using the information to implement strategy.

This is an introductory course in analytics tailored for accounting professionals. Through hands-on work, students learn to ask the right business questions, extract and transform relevant data from an enterprise system, evaluate the integrity of the data, detect patterns and anomalies, apply data analytic techniques, and interpret and present results in order to make data-driven decisions.