Curriculum

Master of Information Technology and Analytics

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

  • 26:198:643 Information Security
  • 22:544:603 Business Data Management
  • 22:544:641 Analytics for Business Intelligence (or 22:544:650 Data Mining)
  • 26:544:688 MIT Capstone Project

Concentrations

At least 3 courses, 3 credits each course

Operations Research and Business Analytics

  • 26:198:685 Introduction to Algorithms & Data Structure (or 16:198:512 Intro to Data Structures and Algorithms)
  • 26:711:651 Linear Programming
  • 26:711:652 Nonlinear Programming
  • 26:711:653 Discrete Optimization
  • 26:960:575 Introduction to Probability
  • 26:960:580 Stochastic Processes

Information Systems

  • 26:198:685 Introduction to Algorithms & Data Structure (or 16:198:512 Intro to Data Structures and Algorithms)
  • 26:198:642 Multimedia Information Systems
  • 22:544:605 Introduction to Software Development
  • 22:630:586 Marketing Management
  • 22:799:659 Supply Chain Solutions with ERP/SAP I

Information Assurance

  • 22:010:577 Accounting for Managers
  • 26:010:653 Auditing
  • 26:198:643 Information Security
  • 26:198:645 Data Privacy
  • 22:544:605 Introduction to Software Development

Elective Courses

At least 4 courses, 3 credits each

  • 26:010:653 Auditing
  • 16:198:552 Computer Networks
  • 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
  • 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
  • 22:544:523 Business Statistics
  • 22:544:575 Data Analysis & Decisions
  • 22:544:605 Introduction to Software Development
  • 22:544:608 Business Forecasting
  • 22:544:638 MITA Internship (0 credits)
  • 22:544:646 Data Analysis & Visualization
  • 22:544:660 Business Analytics Programming
  • 22:544:670 Information Technology Strategy
  • 22:630:604 Marketing Research
  • 26:630:675 Marketing Models
  • 22:630:679 Web Analytics
  • 26:711:530 Semidefinate and Second Order Cone Programming
  • 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
  • 22:799:580 Operations Analysis
  • 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 Management
  • 26:960:575 Introduction to Probability
  • 26:960:576 Financial Time Series
  • 26:960:577 Introduction to Statistical Linear Models

Aspiring Ph.D. Candidates

Students who will later pursue doctoral study in information technology or accounting information systems will have the opportunity to take many of the same courses as students in the Rutgers Business School doctoral programs in information technologyaccounting information systems, and operations research.

If you plan to apply to the RBS Ph.D. program in Information Technology, Accounting Information Systems, or Operations Research, your project should be a doctoral-level research paper, and you should include as many school 26 courses as possible while in the Master of Information Technology program.

Additional Information

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