Business Analytics
This program utilizes skills, technologies, and practices to explore business performance and support data-driven decision-making. It employs descriptive, prescriptive, and predictive modeling, along with other techniques, to extract valuable insights. By combining elements of data analysis, business intelligence, and management science, Business Analytics optimizes organizational strategies and addresses complex challenges.
The program focuses on applying mathematical statistics to business data analysis and prediction, including long- and short-term forecasting methods and market performance analysis. The core courses—Machine Learning for Business (DS 310), Prescriptive Analytics (DS425), Business Forecasting with Python (DS 430), Business Applications Programming (ISM 301), and Data and Information Visualization (ISM 347)—emphasize the application of statistics, machine learning, optimization, programming, and data-driven decision-making.
Dearborn Discovery Core (General Education)
All students must satisfy the University’s Dearborn Discovery Core requirements, in addition to the requirements for the major.
Major Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Required | ||
| DS 310 | Data Mining for Bus Intel | 3 |
| DS 425 | Prescriptive Analytics | 3 |
| DS 430 | Business Forecasting with Python | 3 |
| ISM 301 | Bus Application Programming | 3 |
| ISM 347 | Data and Information Visualization | 3 |
| Electives | ||
| Select a minimum of 6 credit hours from the following: | 6 | |
| Experiential Projects | ||
| CS I for Data Scientists | ||
| CS II for Data Scientists | ||
| Investment Fundamentals | ||
| Corporate Finance Capstone – Advanced Financial Analysis | ||
| Derivative Markets | ||
| Compensation, Performance Management, and HR Analytics | ||
| Database Systems I | ||
| Database Systems II | ||
| Digital Consumer Srch&Mktg | ||
| Marketing Research | ||
| Digital Analytics&Content Marketing | ||
| Analytics & Design of Supply Chains | ||
| Total Credit Hours | 21 | |
The program utilizes skills, technologies, and practices to explore business performance and support data-driven decision-making. It employs descriptive, prescriptive, and predictive modeling, along with other techniques, to extract valuable insights. By combining elements of data analysis, business intelligence, and management science, Business Analytics optimizes organizational strategies and addresses complex challenges.
The minor focuses on applying mathematical statistics to business data analysis and prediction, including long- and short-term forecasting methods and market performance analysis. The core courses—Machine Learning for Business (DS 310), Prescriptive Analytics (DS 425), Business Forecasting with Python (DS 430), Business Applications Programming (ISM 301), and Data and Information Visualization (ISM 347)—emphasize the application of statistics, machine learning, optimization, programming, and data-driven decision-making.
| Code | Title | Credit Hours |
|---|---|---|
| Business Analytics Minor 1 | ||
| Select five courses (15 credits) from the following: 1 | 15 | |
| Introductory Business Statistics using Excel | ||
| Advanced Business Statistics | ||
| Data Mining for Bus Intel | ||
| Prescriptive Analytics | ||
| Business Forecasting with Python | ||
| Bus Application Programming 2 | ||
| Data and Information Visualization 2 | ||
| Total Credit Hours | 15 | |
- 1
Minors requiring 12 credits may share one course with a major. Minors requiring 15 credits or more may share two courses with a major.
- 2
The ISM major can only have one of ISM 301 and ISM 347 share with the Business Analytics minor.