Master in Operations Research and Information Engineering Degree Master of Engineering Program Length 1 Year Issued By Cornell University

Businesses of all types and sizes are awash in data and hungry for skilled analysts and information scientists who can use that data to make insightful, real-time business decisions. Cornell Tech's Master in Operations Research and Information Engineering (ORIE) will provide you with the mathematical modeling and data analysis skills you need to drive the decisions that improve customer satisfaction and operational efficiency.

Learn Where Rigor Meets Innovation

Cornell Tech's ORIE Masters combines Cornell University's academic rigor with the energy and opportunity that come with studying in the heart of New York's tech start-up community.

Led by faculty who are actively shaping the future of Big Data, you'll master the intricacies of data modeling, machine learning and predictive analytics. You'll gain commercial context for your technical expertise through classes in business and entrepreneurship. Working in cross-functional teams with your classmates—who will include ambitious young lawyers, engineers, marketers and product managers— you'll create your own businesses in the Startup Studio and develop real solutions for clients in the Product Studio program. In just one year, you'll graduate with the skills, experience, and network you need to help startups and established companies alike harness data to drive customer value.

Who Should Apply?

Cornell Tech's ORIE Masters is ideal for students with a passion for querying data and using data-derived insights to shape business decisions. The minimum technical requirements are that you have completed one course on optimization, one course of intermediate-level probability and statistics and one course on intermediate-level programming before applying.

A Master of Engineering in Operations Research and Information Engineering (ORIE) is also offered on Cornell's Ithaca campus, with a focus on building traditional math, scientific, and engineering skills, rather than Cornell Tech’s more data-driven approach to teaching mathematical and modeling skills to inform strategic decisions. Learn more.

Topics Covered

  • Optimization Methods
  • Probabilistic Analysis
  • Machine Learning
  • Data Science
  • Modeling Under Uncertainty

Optimization Methods

Credits 3.00

This course covers algorithmic and computational tools for solving optimization problems with the goal of providing decision-support for business intelligence. We will cover the fundamentals of linear, integer and nonlinear optimization. We will emphasize optimization as a large-scale computational tool, and show how to link programming languages, such as Python, Java and C++, with optimization software, such as Gurobi and CPLEX, to develop industrial-strength decision-support systems. We will demonstrate how to incorporate uncertainty into optimization problems. Throughout the course, we will cover a variety of modern applications and show how to deploy large-scale optimization models.

Careers in the Field

  • Analyst
  • Data Scientist
  • Product Manager
  • Startup Founder