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 Computational Data Science concentration provides students with the necessary skills to understand the theory and algorithms utilized in data science and to be able to implement and apply them. 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
Select one of the following:		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
Required Courses
Select three of the following: 1		9.0
CS 560	Fundamentals of Data Science
CS 562	Machine Learning
CS 563	Knowledge Discovery and Data Mining
CS 572	Distributed Databases and Big Data
Electives
Select two electives approved by the student's graduate advisor 2		6.0
CIS 576	Data Management
CIS 580	Digital Society and Computer Law
CS 541	Python Programming for Data Science
CS 560	Fundamentals of Data Science
CS 561	Artificial Intelligence
CS 562	Machine Learning
CS 563	Knowledge Discovery and Data Mining
CS 571	Database Management Systems
CS 572	Distributed Databases and Big Data
ECE 565	Engineering Applications of Machine Learning
ECO 519	Introduction to Econometrics
IME 501	Engineering Cost Analysis
IME 514	Introduction to Operations Research
IME 526	Reliability Engineering
IME 568	Engineering Analytics 1
IME 578	Engineering Analytics 2
IME 583	Production Planning and Control
I B 502	Global Trade Management and Analysis
MTG 502	Logistics Tools and Techniques
MTG 506	Marketing Analytics
MTG 507	Customer Analytics
MTG 624	Marketing Decision Making
MTG 640	Obtaining, Analyzing, and Applying Marketing Information
MTH 510	Numerical Methods I
Q M 526	Business Forecasting
Q M 564	Decision Support Systems
Total Hours		15

¹

Three of the following four courses, that you have not yet taken to fulfill the common core.
Note: If you fulfilled the common core by taking CS 541 Python Programming for Data Science, then one of the 3 courses taken from the list above must be CS 560 Fundamentals of Data Science.

²

For those who choose the thesis option instead of capstone, one elective (3 ch).

On the thesis option:

Interested and qualified students pursuing the Computational Data Science concentration have the option to write a master’s thesis. Students selecting this option are encouraged to choose a thesis advisor and topic as early as possible to plan the thesis development and any needed supporting coursework.

The following policies apply to theses:

• A minimum grade point average of 3.5 in graduate courses taken at Bradley is required for students enrolling in a thesis course, i.e., CS 699 Thesis in Computer Science.
• No student may register for a thesis until 9 hours of graduate courses have been completed in the program.
• Six credit hours of a thesis course are required and, upon completion, the thesis must be defended in an oral examination. The six hours must be in consecutive semester or terms (3+3).
• No grade will be given for a thesis course until after the oral defense. The thesis oral defense substitutes the comprehensive exam that the non-thesis students have to take. 
• A written outline of the thesis project and a tentative schedule must be submitted to and approved by the graduate coordinator and the chair prior to the registration for a thesis course.