Degree Requirements

For the most up-to-date course descriptions please visit the website.

(For curriculum changes starting spring 2021 please see more information at the bottom of this page and on the website.)

Degree Requirements (for students admitted before spring 2021):

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

• three foundation courses
• three core courses from the specific concentration
• four elective courses

Foundation (choose any three of the following four 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  MITA Capstone Project

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

Operations Research and Business Analytics

• 26:198:685  Introduction to Algorithms and Data Structure (or 16:198:513  Design and Analysis of Data Structure 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 and Data Structure (or 16:198:513  Design and Analysis of Data Structure 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 four 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 and Data Structure
• 16:332:568  Software Engineering of Web Applications
• 22:544:523  Business Statistics
• 22:544:575  Data Analysis and Decisions
• 22:544:605  Introduction to Software Development
• 22:544:608  Business Forecasting
• 22:544:646  Data Analysis and 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

If a student plans to apply to the RBS doctoral 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.

Master of Information Technology and Analytics (M.I.T.A.) Program Curriculum (effective spring 2021)

Foundation Courses

Choose any three of the following four courses, 3 credits each:

• 22:544:643  Information Security
• 22:544:603  Business Data Management
• 22:544:641  Analytics for Business Intelligence (or 22:544:650  Data Mining)
• 22:544:613  Introduction to Data Structures and Algorithms (or 16:198:512  Introduction to Data Structures and Algorithms)

Concentrations

Students who opt for a concentration need to complete at least three courses from the respective concentration.

Operations Research and Business Analytics

Data Science and Machine Learning

• 26:198:642  Multimedia Information Systems
• 22:544:605  Introduction to Software Development
• 26:198:641  Advanced Database
• 22:198:646  Data Analysis and Visualization
• 22:544:631  Algorithmic Machine Learning
• 22:544:635  Neural Networks and Deep Learning
• 22:544:634  Optimization Methods for Machine Learning
• 22:544:637  Reinforcement Learning

Cyber Security

• 22:544:643  Information Security
• 26:198:645  Data Privacy
• 22:544:605  Introduction to Software Development
• 22:544:640  Fundamentals of Blockchain and Distributed Ledgers

Elective Courses

Master's-level and Ph.D.-level courses are listed separately. Students registering for a Ph.D.-level course require a special permission.

Master's-level courses:

• 22:544:688  MITA Capstone Project
• 22:544:605  Introduction to Software Development
• 22:544:608  Business Forecasting
• 22:544:638  MITA Internship (0 credits)
• 22:544:646  Data Analysis and Visualization
• 22:544:660  Business Analytics Programming
• 22:544:670  Information Technology Strategy
• 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
• 16:198:520  Introduction to Artificial Intelligence

Ph.D.-level courses:

• 26:711:555  Stochastic Programming
• 26:711:557  Dynamic Programming
• 26:711:685  Special Topics in Operations Research/Management Science
• 26:960:576  Financial Time Series
• 26:960:577  Introduction to Statistical Linear Models
• 22:711:685  Dynamic Pricing and Revenue Management

Policy on Ph.D.-level courses (26 level codes)

The M.I.T.A. students are allowed to take any Ph.D.-level course offered in the Department of Management Science and Information Systems as an elective. However, to protect the quality of those Ph.D.-level courses, which are primarily for Ph.D. students, they are not explicitly mentioned in the electives list. To use Ph.D. and other graduate courses from other departments as electives, students must request and receive approval from the program directors on a case-by-case basis.

Policy on Business Courses in RBS

Some students with a strong prior technical background may be interested in taking graduate courses (e.g., M.B.A. courses) with strong business content from other RBS departments. Qualified M.I.T.A. students may take up to two such courses with the program directors' approval.

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

Course descriptions of courses beginning with school 22 can be found at the M.B.A. Curriculum page, course descriptions for courses beginning with school 26 are listed under the Ph.D. course descriptions.