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Restricted to MS&E majors in their senior year. Students carry out a major project in groups of four, applying techniques and concepts learned in the major. Project work includes problem identification and definition, data collection and synthesis, modeling, development of feasible solutions, and presentation of results. Cardinal Course certified by the Haas Center. Satisfies the WIM requirement for MS&E majors.

Formulation and computational analysis of linear, discrete, and other optimization problems. Strong emphasis on data science and machine learning applications, as well as applications in matching and pricing in online markets. Prerequisite: CME 100 or MATH 51.

Stochastic processes and models in operations research. Discrete and continuous time parameter Markov chains. Queuing theory, inventory theory, simulation. Prerequisite: 120 or equivalent.

Architecture of the Internet and performance engineering of computer systems and networks. Switching, routing and shortest path algorithms. Congestion management and queueing networks. Peer-to-peer networking. Wireless and mobile networking. Information service engineering and management. Search engines and recommendation systems. Reputation systems and social networking technologies. Security and trust. Information markets. Select special topics and case studies. Prerequisites: 111, 120, and CS 106A.

This course provides an introduction to how networks underly our social, technological, and natural worlds, with an emphasis on developing intuitions for broadly applicable concepts in network analysis. The course will include: an introduction to graph theory and graph concepts; social networks; information networks; the aggregate behavior of markets and crowds; network dynamics; information diffusion; the implications of popular concepts such as "six degrees of separation", the "friendship paradox", and the "wisdom of crowds".

Principal methods of economic analysis of the production activities of firms, including production technologies, cost and profit, and perfect and imperfect competition; individual choice, including preferences and demand; and the market-based system, including price formation, efficiency, and welfare. Practical applications of the methods presented. Recommended: 111 or 211, and ECON 50.

Introduction to modern quantitative finance and investments. The course focuses on the basic principles underlying financial decision making which are applicable to all forms of investment: stocks, bonds, real estate, corporate finance, etc., and how they are applied in practice. Topics: interest rates; evaluating investments: present value and internal rate of return; fixed-income markets: bonds, yield, duration, portfolio immunization; term structure of interest rates; measuring risk: volatility, value at risk, expected shortfall; designing optimal security portfolios; the capital asset pricing model. Group projects involving financial market data. No prior knowledge of finance required. Hard prerequisites: MS&E 120 or 220, or CS 109, or STATS 116. MS&E 111 is strongly suggested. Working knowledge of Excel, or Python, or R, or Matlab, or Mathematica is also required.

Key functions of finance in both large and small companies, and the core concepts and tools that provide their foundation. Identifying promising business opportunities. The role of finance in business planning, and in quantifying and managing uncertainty and risk. Determining what to do yourself and what to contract for with partners and suppliers. Valuation, raising money, and optimizing capital structure. Designing performance metrics to align and effectively measure the activities of functional groups and individuals within the firm.

Introduction to hedge fund management. Students actively manage the $1MM Stanford Kudla Fund employing Equity Long/Short, Macro and Quantitative Investment Strategies. Modeled after a hedge fund partnership culture, participation involves significant time commitment, passion for investing, and uncommon teamwork and communication skills. Open to advanced undergraduate and graduate students with continuing participation expectation. Limited to 12 students. Enrollment by application and permission of Instructor. May be repeated for credit.