Accounting Data Analytics (Economics 160) Here is the Claremont McKenna College catalog description: This course will introduce students to the use of analytics tools for deriving insights from accounting data and for more effectively performing audits. Companies produce a wealth of data on customers and company performance, and the next generation of accountants needs to be equipped with tools for organizing and analyzing the data to improve company performance and audit its financial accounts. We will explore the topics of data retrieval, cleanup, preprocessing, and validation, before getting into data visualization, internal and external audit analytics, and predictive modeling/machine learning.
I taught this for the first time in the spring 2019 semester (current syllabus here). The accounting firms have been asking faculty to boost undergrads' data analysis skills, and this course was meant to address those needs. All of the coursework is done in R, and for many students, it represents, their first exposure to anything resembling coding. Students end the course with a group project on whether firms are likely to meet or beat earnings expectations.
Financial Statement Analysis (Economics 154) Here is the Claremont McKenna College catalog description: Combines finance and accounting in a user-oriented, financial statement analysis approach. The goal is to expose students to the usefulness of accounting information for valuation and bankruptcy prediction. Part I introduces ratio analysis and discusses accounting information strengths and limitations. Part II is decision model oriented. It deals with the uses of accounting information for valuation of common stocks and corporate bonds in an efficient market.
I've taught this course since 2007(!), and I use Russell Lundholm and Richard Sloan's textbook (5th edition). It's self-published and quite inexpensive. Not a flashy text, but it's dense with useful information, from two amazing scholars.