- Study and work on
**challenging**and**relevant**problems. - Learn and apply
**mathematical**&**computational**skills to address interesting, useful and timely applications.- These skills are recognized and rewarded in the marketplace by
**employers**&**top graduate schools**. - They will make you a better
**Leader**.

- These skills are recognized and rewarded in the marketplace by

**Probability**: Modeling & understanding of*uncertainty*.**Statistics**: Quantifying*uncertainty*.**Optimization**: MOdeling & understanding of the*tradeoffs*associated with the good fortun of having alternatives (and choosing among them even though they are uncertain).- These skills are recognized and rewarded in the marketplace by
**employers**&**top graduate schools**. - They will make you a better
**Leader**.

- These skills are recognized and rewarded in the marketplace by

Operations Research

- Logistics & Transportation
- Energy Systems
- Telecommunications & eCommerce
- Health Care

Financial Engineering

- Risk Management
- Investment Strategies
- Financial Instruments
- Economic Stimulation

Machine Learning

- Real-time Decision Systems
- Addressing High Dimensional Problems (aka "Big Data")

Fall: 4 Courses

- Math
- Physics
- Chemistry
- Writing (or Frosh Seminar or ???)

Spring: 5 Courses

- Math
- Physics
- Statistics (ORF 245)
- Frosh Seminar (or Writing or ???)
- Other

- ORF 245 - Fundamentals of Statistics
- ORF 307 - Optimization
- ORF 309 - Probability & Stochastic Processes
- ORF 335 - Introduction to Financial Engineering

From... ORF 311 – Stochastic Optimization and Machine Learning in Finance (previously - Optimization Under Uncertainty), ORF 350 – Analysis of Big Data, ORF 360 – Decision Modeling in Business Analytics, ORF 363 – Computing and Optimization for the Physical and Social Sciences, ORF 375/376 - Junior Independent Work, ORF 401 - Electronic Commerce , ORF 405 – Regression and Applied Tim, Series, ORF 406 - Statistical Design of Experiments, ORF 407 – Fundamentals of Queueing Theory, ORF 409 - Introduction to Monte Carlo Simulation, ORF 411 – Sequential Decision Analytics and Modeling, ORF 417 - Dynamic Programming, ORF 418 - Optimal Learning, ORF 435 - Financial Risk Management, ORF 455 – Energy and Commodities Markets, ORF 467 – Transportation Systems Analysis, ORF 473/474 - Special Topics in Operations Research and Financial Engineering, CEE 304 – Environmental Engineering and Energy, CEE 460 - Risk Analysis , CHM 303 – Organic Chemistry I, CHM 304 – Organic Chemistry II, COS 217 - Introduction to Programming Systems, COS 226 - Algorithms and Data Structures, COS 323 - Computing for the Physical and Social Sciences, COS 340 - Reasoning about Computation, COS 402 - Artificial Intelligence and Machine Learning, COS 423 - Theory of Algorithms, COS 485 – Neural Networks: Theory and Application, ECO 310 - Microeconomic Theory: A Mathematical Approach, ECO 311/312 – Macroeconomics: A Mathematical Approach, ECO 317 - The Economics of Uncertainty, ECO 332 – Economics of Health and Health Care, ECO 341 - Public Finance, ECO 342 - Money and Banking, ECO 361 - Financial Accounting, ECO 362 - Financial Investments, ECO 363 - Corporate Finance and Financial Institutions, ECO 418 - Strategy and Information, ECO 462 - Portfolio Theory and Asset Management, ECO 464 - Corporate Restructuring, ECO 466 - Fixed Income: Models and Applications, ECO 467 - Institutional Finance, EEB 324 – Theoretical Ecology, ELE 301 – Designing Real Systems, ELE 381 – Networks: Friends, Money and Bytes, ELE 486 - Digital Communication and Networks, ENV 302 – Practical Models for Environmental Systems, MAE 206 – Introduction to Engineering Dynamics, MAE 433 - Automatic Control Systems, MAE 434 – Modern Control, MAT 320 - Introduction to Real Analysis, MAT 322/APC 350 - Methods in Partial Differential Equations, MAT 375 - Introduction to Graph Theory, MAT 377 - Combinatorial Mathematics, MAT 378 - Theory of Games, MAT 385 - Probability Theory, MAT 391/MAE 305 - Mathematics in Engineering I or MAT 427, (both may not be taken because content is too similar), MAT 392/MAE 306 - Mathematics in Engineering II, MAT 427 - Ordinary Differential Equations, MAT 486 - Random Process, MAT 522 - Introduction to Partial Differential Equations, MOL 345 – Biochemistry, NEU 437 – Computational Neuroscience, NEU 330 – Computational Modeling of Psychological Function

Information Sciences

- ORF 401 – eCommerce
- ORF 411 – Sequential Decision Analytics Modeling
- ORF 418 – Optimal Learning
- COS 217 – Introduction to Programming Systems
- COS 226 – Algorithms & Data Structures
- COS 425 – Database Systems

Engineering Systems

- ORF 409 – Intro to Monte Carlo Simulation
- ORF 411 – Sequential Decision Analytics Modeling
- ORF 467 – Transportation Systems Analysis
- ORF 417 – Dynamic Programming
- MAE 433 – Automatic Control Systems
- ELE 485 – Signal Analysis and Communication Systems

Applied Mathematics

- MAT 375 – Intro to Graph Theory
- MAT 378 – Theory of Games
- MAT 321 – Numerical Methods
- MAE 406 – Partial Differential Equations
- ORF 405 – Regression and Applied Time Series

Financial Engineering

- ORF 311 – Stochastic Optimization and Machine Learning in Finance
- ORF 350 – Analysis of Big Data
- ORF 405 – Regression and Applied Time Series
- ORF 435 – Financial Risk Management
- ECO 362 – Financial Investments
- ECO 465 – Financial Derivatives

Machine Learning

- Statistics
- Pre-Med/Health Care