Course Requirements

Students must complete 30 credits, usually in the form of 10 courses.  The 10 courses must include:

  • 3 foundation course
  • 3 core courses from the specific concentration
  • 4 elective courses


Foundation (choose any 3 of the following 4 courses, 3 credits each)

  • 22:198:603 Business Data Management
  • 22:960:641 Analytics for Business Intelligence (or 26:198:644 Data Mining)
  • 26:198:643 Information Security
  • 26:198:686 Capstone Project


Concentrations (at least 3 courses, 3 credits each course)


Operations Research and Business Analytics

  • 26:960:575 Introduction to Probability
  • 26:198:685 Introduction to Algorithms & Data Structure (or 16:198:513 Design and Analysis of Data Structure and Algorithms)
  • 26:711:651 Linear Programming
  • 26:960:580 Stochastic Processes
  • 26:711:652 Nonlinear Programming
  • 26:711:653 Discrete Optimization
  • 22:390:587 Financial Management


Information Systems

  • 22:198:605 Introduction to Software Development
  • 26:198:685 Introduction to Algorithms & Data Structure (or 16:198:513 Design and Analysis of Data Structure and Algorithms)
  • 26:198:642 Multimedia Information Systems
  • 22:010:623 Enterprise Resource Planning
  • 22:630:586 Marketing Management
     


Information Assurance

  • 22:198:605 Introduction to Software Development
  • 26:198:645 Data Privacy
  • 26:010:653 Auditing
  • 22:835:626 Advanced Auditing & Accounting Information Systems
  • 26:198:643 Information Security
  • 22:010:577 Accounting for Managers 


Elective Courses (at least 4 courses, 3 credits each)

  • 22:010:622 Internet Technology for Business
  • 22:010:623 Enterprise Resource Planning
  • 26:010:653 Auditing
  • 22:140:610 Fundamentals of Intellectual Property
  • 16:198:552 Computer Networks
  • 22:198:604 Computer and Information Systems
  • 22:198:605 Introduction to Software Development
  • 22:198:610 Electronic Commerce
  • 22:198:611 Security for Electronic Commerce
  • 26:198:622 Machine Learning
  • 26:198:641 Advanced Database Systems
  • 26:198:642 Multimedia Information Systems
  • 26:198:643 Information Security
  • 26:198:645 Data Privacy
  • 22:198:670 Information Technology Strategy
  • 26:198:685 Special Topics in Information Systems
    • Applications of Machine Learning to Big Data
    • Big Data: Management,Analysis, and Applications
    • Data-Intensive Analytics
    • Introduction to Algorithms & Data Structure
  • 16:332:568 Software Engineering of Web Applications
  • 22:620:675 Tech Commercialization
  • 22:630:604 Marketing Research
  • 26:630:675 Marketing Models
  • 26:711:530 Semidefinate and Second Order Cone Prgramming
  • 26:711:555 Stochastic Programming
  • 26:711:557 Dynamic Programming
  • 26:711:564 Optimization Models in Finance
  • 26:711:685 Special Topics in Operations Research/Management Science
    • Game Theory
    • Convex Analysis and Optimization
    • Theory of Boolean Functions
  • 22:799:659 Supply Chain Solutions with ERP/SAP I
  • 22:799:660 Supply Chain Solutions with ERP/SAP II
  • 22:799:661 Introduction to Project Management
  • 26:799:660 Supply Chain Modeling and Algorithms
  • 26:799:661 Stochastic Models for Supply Chain Management
  • 26:799:685 Special Topics in Supply Chain and Marketing Science
  • 22:835:626 Advanced Auditing & Accounting Information Systems
  • 22:960:575 Data Analysis & Decisions
  • 26:960:575 Introduction to Probability
  • 26:960:576 Financial Time Series
  • 26:960:577 Introduction to Statistical Linear Models
  • 22:960:646 Data Analysis & Visualization

If a student plans to apply to the RBS PhD program in Information Technology, Accounting Information Systems, or Operations Research, their project should be a doctoral-level research paper, and they should include as many school 26 courses as possible while in the Master of Information Technology program.

You can view current and past schedules for Rutgers here: http://sis.rutgers.edu/soc/ 

Course descriptions of courses beginning with school 22 can be found at the MBA Curriculum page, course descriptions for courses beginning with school 26 are listed under the PhD course descriptions.