The Master in Operations Research and Information Engineering (ORIE) curriculum will prepare you to harness data to make strategic business decisions.

You learn the fundamentals of operations research and master the computational tools you need to provide business intelligence on a large scale. In an educational innovation unique to Cornell Tech, you'll also participate in an immersive Studio experience, in which you'll develop your team-building and leadership skills while developing a new product idea in response to the strategic needs of a real organization and create your own startup.

What Your Schedule Might Look Like

In the fall you’ll take morning classroom courses in Optimization Methods, Modeling Under Uncertainty, and Applied Machine learning. You’ll spend afternoons working on team-based projects in Product Studio and Startup Ideas and learn firsthand from industry leaders in Conversations in the Studio.

In the spring you’ll take morning classroom courses in Service Systems & Online Markets and e-Logistics. You’ll also take one business and one tech elective. In the afternoons, you’ll pursue team-based projects in Startup Studio and Product Management.

Required Curriculum 15.00 Credits

Electives 1.00 Credits

Semester Total 16 Credits

Required Curriculum 10.00 Credits

Electives 6.00 Credits

Semester Total 16 Credits

Program Curriculum

Your core program curriculum.
  • Optimization Methods 3.0

    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.

  • Modeling Under Uncertainty 3.0

    In this course, we will learn how to model randomness, analyze its impact and make optimal decisions when it is present. We will cover stochastic modeling techniques, statistical principles, simulation, and decision-making under uncertainty. Using applications, we will demonstrate how we can use statistical principles to gain insight from data generated by systems with randomness. We will use simulation models to assess the performance of such systems and gauge how it changes in response to our decisions. We will intorudce and use stochastic modeling techniques, such as Markov chains and Brownian motion, to build models of random phenomena and use these to gain understanding and guide decisions. As well as covering theoretical concepts, the course will put substantial emphasis in computaitonal implementation of both simulation and decision-making problems.

  • Applied Machine Learning 3.0

    This course will help students learn and apply key concepts of modeling, analysis and validation from Machine Learning, Data Mining and Signal Processing to analyze and extract meaning from data. Students will implement algorithms and perform experiments on images, text, audio and mobile sensor measurements. They will also gain a working knowledge of supervised and unsupervised techniques including classification, regression, clustering, feature selection, association rule mining and dimensionality reduction.

  • Service Systems & Online Markets 3.0

    This course covers online and phyical service systems with a focus on designing and managing them. When designing service systems, we need to figure out the sales channels to use when offering services, design incentive mechanisms and make tactical capacity decisions. When operating service systems, we need to make real-time pricing decisions, allocate capacity between different needs, make product recommendations and forecast demand and customer behavior. Depending on the application setting, the capacity we manage can be physical, such as seats on an airplane to be allocated to passengers with different willingness to pay amounts, or digital, such as visitors on a webpage to be allocated between advertisers. We will cover ideas from revenue management, experimentation for demand learning, auctions, mechanism design and network theory.

  • e-Logistics 3.0

    Many online and tech businesses face logistics challenges that require optimal management of physical resources. These challenges may take the form of opening fulfillment centers at the the right locations, stocking the right amount of inventory, running optimal number of servers to satisfy computing needs, repositioning bikes in urban bike-sharing systems, and dispatching and repositioning vehicles in online ride-sharing systems. Addressing these challenges often requires building and deploying large-scale optimization models that can make decisions on the fly. We will cover logistics models that allow firms to optimally use its physical resources. From an application perspective, our models will cover the inventory and supply chain theory, network design and transportation logistics. From a methodology perspective, we will use linear and integer programming, stochastic programming, and Markov decision processes. The course will include a number of large case studies that focus on practical implementations.

Electives

Choose electives until semester total is reached.
  • Leadership for Studio 1.0

    This course deals broadly with leadership – of teams, projects, products, businesses, and communities. The course will pay special attention to leadership in the context of digital transformation and its social and economic impacts. Students will learn effective team-building and teamwork strategies, communication and presentation skills, and best practices for building a collaborative, creative and open culture in the workplace. As part of a personal development process, toolkits and exercises will be provided to promote critical thinking and moral reasoning skills. Sessions on social and multicultural awareness and sensitivity will equip students to be global leaders in a digitally-transformed world. In short, this course will cover all aspects of how students can become leaders in a digital economy.

  • Business for Tech 1.0

    Business for Technologists (BT) is a comprehensive introduction to the key aspects of new product development and product management that will provide helpful perspective for technologists working in cross functional teams with business leaders in the marketing, product, finance, legal and business development disciplines. BT focuses both on concepts and frameworks utilizing “solutions architecture” while working on cross functional teams in both agile and waterfall development environments. Students will utilize their team projects as the basis to complete customer development, market segmentation, product placement, construct business models and define “proof points” and milestones that lead to successful outcomes for teams comprised of both technologists and subject matter experts from a broad array of business disciplines. The course will also discuss the development of an “intellectual property suite” and its importance in the new product development process and relevance to the competitive landscape. While the course focuses on scalable businesses, the principles apply to businesses of all sizes. Topics covered will include definition of the market, sales and distribution, competition, business development, project management and milestone based performance tracking. The course culminates in a capstone project of writing a launch plan for a new technology product’s market test.

  • Computer Vision 3.0

    The goal of computer vision is to compute properties of the three-dimensional world from digital images. Problems in this field include reconstructing the three-dimensional shape of an environment, determining how things are moving, and recognizing people and objects and their activities, all through analysis of images and videos. This course will provide an introduction to computer vision, with topics including image formation, feature detection, motion estimation, image mosaics, 3D shape reconstruction, and object and face detection and recognition. Applications of these techniques include building 3D maps, creating virtual characters, organizing photo and video databases, human computer interaction, video surveillance, automatic vehicle navigation and mobile computer vision. This is a project-based course, in which students will implement several computer vision algorithms throughout the semester.

  • Design Thinking 1.0

    This hands-on course will prepare students to be future innovators by teaching Design Thinking, the human-centered design methodology pioneered by IDEO and Stanford d.school founder, David Kelley. Students will work on a team with peers from other disciplines so as to experience the importance of “radical collaboration.” All teams will work on the same challenge, and students will be asked to design an innovative solution to this complex problem.

Studio Interdisciplinary Curriculum

Practicums with other Cornell Tech Masters students.
  • Conversations in the Studio 1.0

    This course features a weekly guest practitioner for a provocative, closed-door discussion with students. The guest practitioners are active entrepreneurs, intrapreneurs, social entrepreneurs, engineers, designers, artists, VCs, lawyers, writers, ethicists, and other diverse leaders who are affecting society through their entrepreneurial efforts. Conversations take place in the Cornell Tech Studio and are moderated each week by a randomly assigned group of students who come prepared with questions and discussion topics. This is not a lecture: it's a weekly wake-up call.

  • Startup Ideas 1.0

    This studio-based course helps students develop their ability to imagine, recognize, develop and improve startup ideas. In each class, students learn a different approach to product ideation or product critique, then practice that approach, working in many different teams -- often with the advice of visiting entrepreneurs, VCs, domain experts, and other practitioners. Students invent and explore hundreds of startup ideas, and help each other evaluate and improve those ideas. By the end of the course, students self-organize into co-founding teams around specific startup ideas that they will pursue in Startup Studio the following semester.

  • Product Studio 3.0

    In Product Studio you and a team of your classmates will respond to a "Company Challenge" by developing, testing, and presenting a new product or business idea. Previous challenges have been posed by organizations as diverse as the Robin Hood Foundation, Uber, Weight Watchers and Bloomberg.

  • Conversations in the Studio 1.0

    This course features a weekly guest practitioner for a provocative, closed-door discussion with students. The guest practitioners are active entrepreneurs, intrapreneurs, social entrepreneurs, engineers, designers, artists, VCs, lawyers, writers, ethicists, and other diverse leaders who are affecting society through their entrepreneurial efforts. Conversations take place in the Cornell Tech Studio and are moderated each week by a randomly assigned group of students who come prepared with questions and discussion topics. This is not a lecture: it's a weekly wake-up call.

  • Product Management 1.0

    This studio-based course helps students learn about and develop product management (PM) skills by putting those abilities immediately to use on their Startup Studio projects. In each session, students learn about a different aspect of product management, product design, or technology development, then practice applying it to their Startup Studio projects, working in the Studio with their project teams and with the help and critique of the practitioner instructors and sometimes visiting practitioners. By the end of the semester, students will have developed and practiced many of the fundamental product management skills required to develop new technology products, and their Startup Studio projects will have greatly benefited from the practice.

  • Startup Studio 3.0

    In Startup Studio you and a team of your classmates will develop your own new product or startup idea. You'll experience the entire process, from developing your idea, to prototyping and testing, to pitching to investors. You can even apply for a Startup Award that will provide funding and other support to help you turn your Startup Studio project to a real business.

  • Leadership for Studio 1.0

    This course deals broadly with leadership – of teams, projects, products, businesses, and communities. The course will pay special attention to leadership in the context of digital transformation and its social and economic impacts. Students will learn effective team-building and teamwork strategies, communication and presentation skills, and best practices for building a collaborative, creative and open culture in the workplace. As part of a personal development process, toolkits and exercises will be provided to promote critical thinking and moral reasoning skills. Sessions on social and multicultural awareness and sensitivity will equip students to be global leaders in a digitally-transformed world. In short, this course will cover all aspects of how students can become leaders in a digital economy.

Open Studio

Show off your semester of studio work to industry insiders.

LEARN MORE

Program Courses

Applied Machine Learning 3.0 CS 5785

This course will help students learn and apply key concepts of modeling, analysis and validation from Machine Learning, Data Mining and Signal Processing to analyze and extract meaning from data. Students will implement algorithms and perform experiments on images, text, audio and mobile sensor measurements. They will also gain a working knowledge of supervised and unsupervised techniques including classification, regression, clustering, feature selection, association rule mining and dimensionality reduction.

Optimization Methods 3.0 ORIE 5380

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.

Modeling Under Uncertainty 3.0 ORIE 5530

In this course, we will learn how to model randomness, analyze its impact and make optimal decisions when it is present. We will cover stochastic modeling techniques, statistical principles, simulation, and decision-making under uncertainty. Using applications, we will demonstrate how we can use statistical principles to gain insight from data generated by systems with randomness. We will use simulation models to assess the performance of such systems and gauge how it changes in response to our decisions. We will intorudce and use stochastic modeling techniques, such as Markov chains and Brownian motion, to build models of random phenomena and use these to gain understanding and guide decisions. As well as covering theoretical concepts, the course will put substantial emphasis in computaitonal implementation of both simulation and decision-making problems.

Leadership for Studio 1.0 NBAY 6800

This course deals broadly with leadership – of teams, projects, products, businesses, and communities. The course will pay special attention to leadership in the context of digital transformation and its social and economic impacts. Students will learn effective team-building and teamwork strategies, communication and presentation skills, and best practices for building a collaborative, creative and open culture in the workplace. As part of a personal development process, toolkits and exercises will be provided to promote critical thinking and moral reasoning skills. Sessions on social and multicultural awareness and sensitivity will equip students to be global leaders in a digitally-transformed world. In short, this course will cover all aspects of how students can become leaders in a digital economy.

Startup Studio 3.0 CS 5999

In Startup Studio you and a team of your classmates will develop your own new product or startup idea. You'll experience the entire process, from developing your idea, to prototyping and testing, to pitching to investors. You can even apply for a Startup Award that will provide funding and other support to help you turn your Startup Studio project to a real business.

Product Studio 3.0 CS 5999

In Product Studio you and a team of your classmates will respond to a "Company Challenge" by developing, testing, and presenting a new product or business idea. Previous challenges have been posed by organizations as diverse as the Robin Hood Foundation, Uber, Weight Watchers and Bloomberg.

Elective Courses

Service Systems & Online Markets 3.0

This course covers online and phyical service systems with a focus on designing and managing them. When designing service systems, we need to figure out the sales channels to use when offering services, design incentive mechanisms and make tactical capacity decisions. When operating service systems, we need to make real-time pricing decisions, allocate capacity between different needs, make product recommendations and forecast demand and customer behavior. Depending on the application setting, the capacity we manage can be physical, such as seats on an airplane to be allocated to passengers with different willingness to pay amounts, or digital, such as visitors on a webpage to be allocated between advertisers. We will cover ideas from revenue management, experimentation for demand learning, auctions, mechanism design and network theory.

e-Logistics 3.0

Many online and tech businesses face logistics challenges that require optimal management of physical resources. These challenges may take the form of opening fulfillment centers at the the right locations, stocking the right amount of inventory, running optimal number of servers to satisfy computing needs, repositioning bikes in urban bike-sharing systems, and dispatching and repositioning vehicles in online ride-sharing systems. Addressing these challenges often requires building and deploying large-scale optimization models that can make decisions on the fly. We will cover logistics models that allow firms to optimally use its physical resources. From an application perspective, our models will cover the inventory and supply chain theory, network design and transportation logistics. From a methodology perspective, we will use linear and integer programming, stochastic programming, and Markov decision processes. The course will include a number of large case studies that focus on practical implementations.