Electives

As an iMSA student you will be taking 12 semester credits in elective courses. At least 4 semester elective credits must be in non-accountancy courses.

Accountancy Electives

ACCY 506 Advanced Financial Reporting

Current authoritative accounting standards and applications to accounting practice. Topics do not represent the full range of financial reporting issues, but are selected based on relevance of the underlying business transaction, complexity of the topic, consistency of applicable standard with underlying reporting concepts, and transferability of the standard to other accounting issues. Total Credit Hours: 4

ACCY 507 Taxation of Business Entities

The first half of the course provides an introduction to the U.S. federal income taxation of corporations and their shareholders. The course focuses on the relevant provisions of Subchapter C of the Internal Revenue Code, as well as related Treasury Regulations and judicial opinions, governing corporate formation, operations, distributions, and liquidation. The second half of the course provides an introduction to the U.S. federal income taxation of pass-through business entities, including Subchapter S corporations, partnerships, and limited liability companies. It focuses on the relevant provisions of Subchapters S and K of the Internal Revenue Code, as well as related Treasury Regulations and judicial opinions, governing the formation, operation, and termination of pass-through entities. Practical in-class study problems facilitate self-discovery of technical tax knowledge along with the development of a variety of professional skills and attitudes.  Total Credit Hours: 4

ACCY 516 Professional Responsibility and Ethics for Accountants

This course covers key principles of accountants’ professional responsibility in their jobs, organizations, and careers, and adopts both theoretical and practical perspectives of the role of ethics and morals within the accounting discipline. The course begins with a general overview of these key constructs and principles, including various philosophies from a variety of disciplines and cultures. Next, the course provides a historical perspective of major instances of accounting-related “failures” and “successes” in the area of professional responsibility and ethics. This historical perspective provides the underlying reasoning for many contemporary codes of conduct, ethics, and professional guidelines. A variety of experiential learning opportunities will help students explore and develop their own perspective on ethics and morals, and how these principles affect their professional roles, responsibilities, and choices. Total Credit Hours: 3

ACCY 569 Data Driven Decisions for Accounting

This course prepares students to use analytic software to explore, visualize, and statistically analyze accounting data. It first introduces students to the need for analytics in accounting by sampling problems from different accounting domains. Students then learn to frame problems in a way that can be answered by using data, and how to structure data so that it’s ready to be analyzed. Students create interactive visualizations in Excel and Tableau to examine data, identify patterns and relationships in the data, and then communicate the findings. This course also introduces students to statistical analyses (i.e. regression and clustering) for quantifying patterns and relationships that are observed in the data. Finally, this course introduces accounting students to programming via macros and the VisualBasic editor in Excel to automate data preparation and data analyses. Total Credit Hours: 2

ACCY 576 Data Preparation for Accounting

This course focuses on developing Python skills for assembling business data, taught within the context of multiple accounting settings (e.g., financial statement data, stock data, loan data, point-of-sale data, etc.). The first half of the course uses an integrated development environment to automate data analytic tasks. We discuss how to manage code and share results within Jupyter Notebook, a popular development environment for data analytic software like Python and R. We then review some fundamental programming skills, such as mathematical operators, functions, conditional statements and loops using Python software. The second half of the course focuses on assembling data for machine learning purposes. We introduce students to Pandas dataframes and Numpy for structuring and manipulating data. We then analyze the data using visualizations and linear regressions. Finally, we explain how to use Python for interacting with SQL data. Total Credit Hours: 2

ACCY 577 Machine Learning for Accounting

This course introduces machine learning algorithms and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses feature importance and model optimization. This course provides an entry point for students to be able to apply proper machine learning algorithms on business related datasets to solve various problems. By end of the course, combined with the skills learned from ACCY 576, students should be able to complete an entire data analytics process with Python. Total Credit Hours: 2

MBA 565- Infonomics

This course introduces infonomics – a collective of concepts, principles, techniques, and models that lead managers to value, handle and deploy information as an actual enterprise asset. The course begins with an overview of information, its role in the firm, and its unique economic properties. Students will explore different ways to optimize the economic benefits from information, including monetizing information and using analytics to enhance information’s utility. Next, formal information asset management and valuation methods that leverage well-honed approaches from other asset disciplines will be discovered, developed and studied. The course covers a variety of inter-related principles and concerns, including information rights and privacy issues, the applicability of core microeconomics concepts, and emerging information-related roles and structures to help organizations become more data-driven. Total Credit Hours: 4

ACCY 578 Accounting Analytics Applications

ACCY 578-A (Fall) allows students to use analytics-based tools in a performance-evaluation system context. Specifically, students will investigate and assess the strengths and weaknesses of a firm’s implementation of a new performance evaluation system. Total Credit Hours: 1

ACCY 578-B (Fall) explores fraud analytics. Specifically, students will learn and apply fraud analytical techniques, with a special focus on the interaction between analytical tools and human judgment. Total Credit Hours: 1

In ACCY 578-1 (Spring), students will complete an extensive case, in which they must analyze purchase transactions. Students will use both Excel and Python, and communicate the results of their analyses via data visualization techniques. Total Credit Hours: 1

In ACCY 578-2 (Spring), students will use public data available from the City of Chicago to help taxicab companies – and individual drivers – maximize revenue. The focus of this course is on developing skills to use unstructured data. Total Credit Hours: 1

Non-Accountancy Electives

Most non-accountancy electives are eight-week, four-credit hour courses and can be taken year round (fall, spring, and summer semesters.)  You can view a list of currently available elective course here.