ACCT 661: Advanced Accounting Analytics I Master Syllabus
Course Instructor: Faculty Directory
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Course Website: Canvas
Course Description
This course provides an advanced study of how accounting analytics and emerging artificial intelligence technologies are used to solve business problems. Emphasis is placed on developing an analytics mindset and applying techniques to extract, transform, analyze, and visualize accounting data to support informed decision-making. These techniques are implemented using contemporary platforms commonly used in accounting practice (e.g., Microsoft Excel, Alteryx, Tableau, and Python). Use cases for generative and agentic AI platforms are also introduced.
Course Objectives
The overall objective of this course is to enable students to cultivate their analytics mindset in preparation for entering a rapidly changing accounting landscape. More specifically,
- Students will be able to define accounting data and information as well as understand how this definition is expanding into new financial and non-financial domains.
- Students will build upon their understanding of the importance of the analytics mindset in transforming accounting data to information for decision making.
- Students will be able to identify accounting and business questions that can be practically addressed using analytics, generative artificial intelligence, and emerging agentic AI tools.
- Students will learn how to effectively extract, transform, and load data in preparation for analysis, with attention to data quality, structure, usability, and the opportunities and limitations of AI-assisted workflows.
- Students will understand the differences among descriptive, diagnostic, predictive, and prescriptive analytics and how these approaches can be applied to accounting-related analytic tests.
- Students will learn to analyze and interpret results and communicate insights through effective data storytelling and visualization techniques while applying appropriate professional judgment.
- Students will develop digital acumen by applying accounting analytics techniques using contemporary platforms commonly used in practice.
Required Textbook and Online Resources
Data Analytics for Accounting, 3rd ed., by Richardson, Teeter, and Terrell (McGraw Hill)
The textbook can be purchased from any source in any format (print or eBook), and you do not need to purchase the McGraw Hill Connect online platform with the textbook. This text will be augmented by other readings and resources provided by Prof. Maex. These materials will be described in the weekly learning modules on Canvas and are available at no charge.
DataCamp: Use of DataCamp will be described in the weekly learning modules on Canvas and a student subscription is available at no charge and students will receive an email invite to a DataCamp classroom entitled Advanced Accounting Analytics I. DataCamp Course certificates are encouraged to be posted on your professional profile (e.g., LinkedIn).
Course Site
The Canvas site will be updated regularly. This site will be used for file storage and retrieval, lecture materials, quizzes, discussions, and student grading. Ignorance of course changes due to failure to access the site or participate in the lessons is not an acceptable excuse.
Grading
| Grade Component | Points |
|---|---|
| Exams (2x200) | 400 |
| Assignments | 400 |
| Other Submissions | 140 |
| Participation | 60 |
| Total Course Points | 1000 |
Grades will be determined using a straight scale as follows. Any discussions regarding your grade must be in scheduled office hours and not by email. Keep in mind that the grade “A” is reserved for work of excellent quality.
| Points | Grade |
|---|---|
| 980 to 1000 | A+ |
| 940 to 979 | A |
| 900 to 939 | A- |
| 870 to 899 | B+ |
| 810 to 869 | B |
| 800 to 809 | B- |
| 700 to 799 | C |
| Below 700 | F |
Deliverables
What you gain from this course will depend on your effort and enthusiasm in completing the course activities and deliverables. You will need to actively participate in the weekly learning modules. Instructions and schedules for activities will be made available within each module. Please review the deliverable instructions carefully.
Exams: Two exams will be given during the course (one in the early part of Week 4 and one in the early part of Week 7). They will be given online and make use of Honorlock. More details on the exam format and structure will be provided in the weeks leading up to the exam.
Assignments: Four assignments applying the analytics skills studied in class will be completed over the course of the semester. More information on these assignments will be presented in class.
Other Weekly Submissions: Other weekly submissions (quizzes, exercises, etc.) will be low stakes in nature and intended to ensure that students are synthesizing course content throughout the course.
Student Responsibilities Specific to this Course
This course is delivered in an eight-week module. This means that the course is accelerated. A regular semester course is covered in 15 weeks. Thus, to do well, you should plan on spending a minimum of 15 to 18 hours a week on this course. Learning technology is time intensive, and you cannot learn simply by reading a book or attending class. You need to work your schedule to incorporate the time necessary to complete pre- and post-class activities on time. Many of you have experiences where everything that can go wrong while working on a computer goes wrong. Do not put off completing course requirements until the last minute.
Master of Science in Accounting Program Learning Goals
- Professional Communications. Our students will communicate effectively to professional audiences in both written and oral forms.
- Technical Skills and Knowledge. Our graduates will demonstrate and apply technical knowledge of accounting.
- Global Perspective. Our students will demonstrate an understanding of the role of accounting in the global business environment.
- Technology and Analytics Skills. Our students will develop advanced technology skills to support decision-making processes in accounting.
- Ethics. Our graduates will understand the importance of ethical conduct.
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