Master of Science - Data Science and Analytics - Logistics Analytics Concentration

The logistics analytics concentration emphasizes the management of data throughout the supply chain.  The master’s degree in data science and analytics is a 30 credit-hour program. Learn how to extract knowledge and insights from both structured and unstructured data in order to enhance a company's supply chain efficiency, improve its productivity and grow its market share by providing decision-makers with actionable data insights. Learn how this information is used to determine supply chain priorities and define key performance indicators.  Applying data science in the context of marketing logistics and supply chain decision making will help you learn how to communicate scientific insights to decision makers in the language of business.

For more information about the program, please reach out to us at or via phone (309) 215-5588 (available on WhatsApp).

Make a Strategic Career Decision

Analytics are your entry point to becoming a real decision-maker in support of supply chain professionals. But why go with Bradley? As an interdisciplinary program, similar to what you will discover in industry, you will learn how to work on teams of professionals with different skill sets and knowledge in order to solve problems.  You will have opportunities for independent study, internships plus you will work on real consulting projects with business clients in different industries.

Graduate Admission Requirements

Learn more about graduate admission standards and application requirements on our Requirements page.

Program Admission Requirements

  • 15 years of education minimum (Bachelor degree in any discipline)
  • No GMAT or GRE is required.
  • Completion of at least one semester of calculus

Graduate Program Requirements

Core Courses - 15 hrs.

  • IME 511: Probability & Statistics for Analytics - 3 hrs
  • CS 541: Python Programming for Data Science – 3 hrs or CS 560: Fundamentals of Data Science - 3 hrs
  • CS 571: Database Management Systems or IME 568: Engineering Analytics I - 3 hrs.
  • MIS 573: Data Visualization for Business Analytics - 3 hrs.
  • MIS 590 Business Analytics Consulting Project – 3 ch OR (CS 594 Capstone Project for Data Science - 3 ch OR CS 699 Thesis) OR (IME 690 Capstone Project for Engineering Analytics OR IME 691 Research/Practicum – 3 ch OR IME 699 Thesis)

Concentration Required Courses - 15 hrs.

  • IB 502 Global Trade Management and Analysis - 3 ch
  • MTG 502 Logistics Tools and Techniques - 3 ch
  • MTG 506 Marketing Analytics or MTG 507 Customer Analytics – 3 ch
  • Choose (2) Electives – 6 ch

Possible electives for the Business Analytics concentration include courses required by the other concentrations, or additional courses listed below, or courses approved by the department chair. It is the responsibility of the student to ensure they have met the prerequisites for their elective courses.

  • CIS 576 Data Management
  • CIS 580 Digital Society and Computer Law
  • CS 541 Python 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 Econometrics
  • IME 501 Engineering Cost Analysis
  • IME 514 Introduction to Operations Research
  • IME 526 Reliability Engineering
  • IME 561 Simulation of Manufacturing & Service Systems
  • IME 568 Engineering Analytics I
  • IME 578 Engineering Analytics II
  • IME 583 Production Planning and Control
  • MIS 613 Advanced Algorithms for Business
  • IB 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
  • MTH 511 Numerical Methods II
  • Q M 526 Business Forecasting
  • Q M 564 Decision Support Systems