MAcc Curriculum (30 hours)-Beginning Fall 2015
The UTC MAcc Program requires that a student complete a minimum of 30 semester hours (18 hours of core courses and 12 hours of elective courses) in graduate coursework as follows:
Core Courses (18 hours)
- ACC 5310 - Advanced Managerial Accounting & Control
- ACC 5360 - Advanced Accounting Information Systems
- ACC 5420 - Tax Research and Advanced Tax Topics
- ACC 5470 - Financial Accounting Theory & Issues
- ACC 5520 - Advanced Auditing
- ACC 5891 - Professional Accounting Certification (1 hour)
- ACC 5892 - Professional Accounting Certification (2 hours)
Elective Courses (12 hours)
OPTION 1: Four approved electives (12 hours)
Students may select electives from the areas of accounting, business administration, finance, marketing, or management.
- Three of the 12 hours must be in accounting.
- The students may select the remaining electives from the areas of accounting, business administration, finance, marketing, and/or management
The offering of electives is determined by student demand. Electives must be chosen in consultation with and approved by the MAcc advsier.
OPTION 2: Forensic Data Analytics Concentration (12 hours)
- ACC 5521 Forensic Accounting
- MGT 5140 Business Database Systems Management
- MGT 5190 Data Mining & Analytics
- MGT 5200 Advanced Data Analytics
Forensic data analytics is an accounting specialization that is quickly increasing in demand in the accounting field. Auditing and forensic accounting independently test financial assertions through increasingly digital evidence located in multiple accounting information systems. The forensic data analytics concentration provides the technical knowledge of basic business analytics concepts, database management, forensic accounting methods, SAS skills, and advanced data analytics. These are essential skills for effectively auditing internal control and large volume transaction data sets. In addition, this concentration covers basic and advanced statistical and quantitative analysis, exploratory and predictive models, and fact-based management to generate knowledge and drive decision and actions.