Business Data Analytics, Certificate
Certificate in Business Data Analytics (325005C)
The certificate in Business Data Analytics allows a student to develop fundamental competencies in data sourcing, data acquisition, data organization, data analysis, data applications, and data analytic software such as SAS and R.
This certificate program requires a total of 12-15 credits and is designed for motivated students who have an interest in learning the fundamentals of econometrics, forecasting and other data analytics applications.
Requirements for Admission
Students need to meet with an advisor in the College of Business to declare this certificate. No specific requirements needed. However, all certificate rules of the College of Business apply towards this Business Data Analytics certificate.
College of Business Undergraduate Programs
College of Business room 260
The following information has official approval of the Department of Economics and the College of Business, but is intended only as a guide. Completion of this certificate is contingent upon many factors, including but not limited to: class availability, total number of required credits, work schedule, finances, family, course drops/withdrawals, successfully passing courses, prerequisites, among others.
College of Business Policies for Certificates:
- Complete all certificate requirements prior to graduation.
- Earn a 2.0 GPA in all certificate coursework.
- Maintain a cumulative 2.0 GPA in all undergraduate coursework.
- Complete all prerequisites for each course.
- Courses may not be taken as pass/fail.
- Complete at least 6 additional credits not needed for any other major, minor, or certificate.
- Earn at least 9 credits at The University of Akron in the College of Business.
- Declare the certificate in the Business Undergraduate Advising Office, College of Business room 260.
|Principles of Microeconomics|
and Principles of Macroeconomics
|or ECON:244||Introduction to Economic Analysis|
|ECON:325||Applied Econometrics I||3|
|ACCT:250||Spreadsheet Modeling & Decision Analysis||3|