Dr. Krishnanand (Kris) Y. Maillacheruvu, Interim Dean
Foster College of Business & Caterpillar College of Engineering and Technology
Dr. Sherri Morris, Interim Dean
College of Liberal Arts and Sciences
Bradley University offers an interdisciplinary graduate program leading to the degree of master of science in Data Science and Analytics. This course of study is designed to prepare students for professional careers in the field or for further study and research.
The Data Science and Analytics graduate program provides students with the necessary skills to effectively use large data sets to solve problems and potentially find new insights.
Students can concentrate their study in various application areas including: 1) business analytics, 2) computational data science, 3) engineering analytics and 4) logistics analytics.
Admission requirements to the Data Science and Analytics program are given below:
- completed at least one semester of calculus
- for the computational data science and engineering analytics concentration, applicants must submit GRE General Test scores taken within the last five years. The applicant may request a GRE waiver under certain circumstances.
The Business Analytics concentration provides students with the necessary skills to analyze organizational data to aid in business decision-making. The concentration is comprised of 15 semester hours of study.
In addition to satisfying all the Graduate Education requirements for the degree, all candidates for the master’s degree must satisfy the following departmental requirements:
- At least 30 hours of graduate-level coursework.
- No "D" grades can be counted in the completion of requirements for the degree.
- Every student must take a comprehensive exam as defined and administered by the concentration department that the student is in.
- Students may register for only three courses per semester. Any exceptions must be approved by the appropriate department chair.
- To satisfy the core (breadth) requirement, five courses or 15 credit hours must be taken:
Core (Breadth) Requirements
Course List
| Code |
Title |
Hours |
| IME 511 | Probability and Statistics for Analytics | 3.0 |
| CS 541 | Python Programming for Data Science | 3.0 |
| or CS 560 | Fundamentals of Data Science |
| CS 571 | Database Management Systems | 3.0 |
| or IME 568 | Engineering Analytics 1 |
| MIS 573 | Data Visualization for Business Analytics | 3.0 |
| 3.0 |
| MIS 590 | Capstone Project for Business Analytics | 3.0 |
| CS 594 | Capstone Project for Data Science | 3.0 |
| or CS 699 | Thesis in Computer Science |
| IME 690 | Engineering Data Analytics Capstone | 3.0 |
| or IME 691 | Research |
To satisfy depth requirements, the student must take 15 credit hours from the concentration listed below. No course used to satisfy the core requirement may be counted as one of the courses in this requirement.
Concentration Requirements
Course List
| Code |
Title |
Hours |
| MIS 571 | Applied Machine Learning for Business | 3.0 |
| Q M 526 | Business Forecasting | 3.0 |
| Q M 564 | Decision Support Systems | 3.0 |
| 1 | 6.0 |
| Data Management | |
| Digital Society and Computer Law | |
| Python Programming for Data Science | |
| Fundamentals of Data Science | |
| Artificial Intelligence | |
| Machine Learning | |
| Knowledge Discovery and Data Mining | |
| Database Management Systems | |
| Distributed Databases and Big Data | |
| Engineering Applications of Machine Learning | |
| Introduction to Econometrics | |
| Engineering Cost Analysis | |
| Introduction to Operations Research | |
| Reliability Engineering | |
| Simulation of Manufacturing & Service Systems | |
| Engineering Analytics 1 | |
| Engineering Analytics 2 | |
| Production Planning and Control | |
| Global Trade Management and Analysis | |
| Logistics Tools and Techniques | |
| Marketing Analytics | |
| Customer Analytics | |
| Marketing Decision Making | |
| Obtaining, Analyzing, and Applying Marketing Information | |
| Numerical Methods I | |
| Business Forecasting | |
| Decision Support Systems | |
| Total Hours | 15 |
