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MS&E 111X: Introduction to Optimization (Accelerated) (ENGR 62X, MS&E 211X)

Optimization theory and modeling. The role of prices, duality, optimality conditions, and algorithms in finding and recognizing solutions. Perspectives: problem formulation, analytical theory, computational methods, and recent applications in engineering, finance, and economics. Theories: finite dimensional derivatives, convexity, optimality, duality, and sensitivity. Methods: simplex and interior-point, gradient, Newton, and barrier. Prerequisite: CME 100 or MATH 51 or equivalent.
Terms: Aut, Win | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 120: Probabilistic Analysis

Concepts and tools for the analysis of problems under uncertainty, focusing on focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, random variables, distributions, conditioning, expectation, change of variables, and limit theorems. Prerequisite: CME 100 or MATH 51.
Terms: Aut | Units: 5 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

MS&E 140: Accounting for Managers and Entrepreneurs (MS&E 240)

Non-majors and minors who have taken or are taking elementary accounting should not enroll. Introduction to accounting concepts and the operating characteristics of accounting systems. The principles of financial and cost accounting, design of accounting systems, techniques of analysis, and cost control. Interpretation and use of accounting information for decision making. Designed for the user of accounting information and not as an introduction to a professional accounting career. Enrollment limited. Admission by order of enrollment.
Terms: Aut, Win, Spr, Sum | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 145: Introduction to Finance and Investment

Introduction to financial markets and empirical evidence that is useful for investment decisions. Time-value of money: understanding basic interest rates, evaluating investments with present value and internal rates of return.Covers basic financial products, including bonds, stocks, derivatives, index funds and real estate. Group discussions and debate approach to learn the following topics: how the prices of financial products are influenced by exogenous factors and human psychology, dynamic formation of financial products portfolio to mitigate risk, finding arbitrage opportunity, alternate ways to obtain financing for a business venture and personal financial investment decisions. Students will engage in a stock market simulation with real data. No prior knowledge of finance is required. Prerequisites: basic preparation in probability and statistics.
Terms: Aut | Units: 4 | Grading: Letter or Credit/No Credit

MS&E 149: Hedge Fund Management

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 repeat for credit.
Terms: Aut, Win, Spr | Units: 1-2 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Borland, L. (PI)

MS&E 178: The Spirit of Entrepreneurship

Is there more to entrepreneurship than inventing the better mouse trap? This course uses the speakers from the Entrepreneurial Thought Leader seminar (MS&E472) to drive research and discussion about what makes an entrepreneur successful. Topics include venture financing, business models, and interpersonal dynamics in the startup environment. Students meet before and after MS&E 472 to prepare for and debrief after the sessions. Enrollment limited to 60 students. Application available at first class session.
Terms: Aut, Win, Spr | Units: 2 | Repeatable for credit | Grading: Letter or Credit/No Credit

MS&E 180: Organizations: Theory and Management

For undergraduates only; preference to MS&E majors. Classical and contemporary organization theory; the behavior of individuals, groups, and organizations. Limited enrollment. Students must attend and complete an application at the first class session.
Terms: Aut | Units: 4 | Grading: Letter (ABCD/NP)

MS&E 193: Technology and National Security: Past, Present, and Future (INTLPOL 256, MS&E 293)

Explores the relation between technology, war, and national security policy from early history to modern day, focusing on current U.S. national security challenges and the role that technology plays in shaping our understanding and response to these challenges. Topics include the interplay between technology and modes of warfare; dominant and emerging technologies such as nuclear weapons, cyber, sensors, stealth, and biological; security challenges to the U.S.; and the U.S. response and adaptation to new technologies of military significance.
Terms: Aut | Units: 3-4 | UG Reqs: WAY-SI | Grading: Letter or Credit/No Credit

MS&E 208A: Practical Training

MS&E students obtain employment in a relevant industrial or research activity to enhance professional experience, consistent with the degree program they are pursuing. Students submit a statement showing relevance to degree program along with offer letter to the Student Services Office before the start of the quarter, and a 2-3 page final report documenting the work done and relevance to degree program at the conclusion of the quarter. Students may take each course once. To receive a permission code to enroll, please submit this form: http://web.stanford.edu/~lcottle/forms/CPTapp.fb with statement and offer letter.
Terms: Aut, Win, Spr, Sum | Units: 1 | Grading: Satisfactory/No Credit

MS&E 208B: Practical Training

MS&E students obtain employment in a relevant industrial or research activity to enhance professional experience, consistent with the degree program they are pursuing. Students submit a statement showing relevance to degree program along with offer letter to the Student Services Office before the start of the quarter, and a 2-3 page final report documenting the work done and relevance to degree program at the conclusion of the quarter. Students may take each course once. To receive a permission code to enroll, please submit this form: http://web.stanford.edu/~lcottle/forms/CPTapp.fb with statement and offer letter.
Terms: Aut, Win, Spr, Sum | Units: 1 | Grading: Satisfactory/No Credit

MS&E 208C: Practical Training

MS&E students obtain employment in a relevant industrial or research activity to enhance professional experience, consistent with the degree program they are pursuing. Students submit a statement showing relevance to degree program along with offer letter to the Student Services Office before the start of the quarter, and a 2-3 page final report documenting the work done and relevance to degree program at the conclusion of the quarter. Students may take each course once. To receive a permission code to enroll, please submit this form: http://web.stanford.edu/~lcottle/forms/CPTapp.fb with statement and offer letter.
Terms: Aut, Win, Spr, Sum | Units: 1 | Grading: Satisfactory/No Credit

MS&E 208D: Practical Training

MS&E students obtain employment in a relevant industrial or research activity to enhance professional experience, consistent with the degree program they are pursuing. Students submit a statement showing relevance to degree program along with offer letter to the Student Services Office before the start of the quarter, and a 2-3 page final report documenting the work done and relevance to degree program at the conclusion of the quarter. Students may take each course once. To receive a permission code to enroll, please submit this form: http://web.stanford.edu/~lcottle/forms/CPTapp.fb with statement and offer letter.
Terms: Aut, Win, Spr, Sum | Units: 1 | Grading: Satisfactory/No Credit

MS&E 208E: Part-Time Practical Training

MS&E students obtain employment in a relevant industrial or research activity to enhance professional experience, consistent with the degree program they are pursuing. Students submit a statement showing relevance to degree program along with offer letter to the Student Services Office before the start of the quarter, and a 2-3 page final report documenting the work done and relevance to degree program at the conclusion of the quarter. Course may be repeated for credit. To receive a permission code to enroll, please submit this form: http://web.stanford.edu/~lcottle/forms/CPTapp.fb with statement and offer letter.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

MS&E 211X: Introduction to Optimization (Accelerated) (ENGR 62X, MS&E 111X)

Optimization theory and modeling. The role of prices, duality, optimality conditions, and algorithms in finding and recognizing solutions. Perspectives: problem formulation, analytical theory, computational methods, and recent applications in engineering, finance, and economics. Theories: finite dimensional derivatives, convexity, optimality, duality, and sensitivity. Methods: simplex and interior-point, gradient, Newton, and barrier. Prerequisite: CME 100 or MATH 51 or equivalent.
Terms: Aut, Win | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 213: Introduction to Optimization Theory (CS 269O)

Introduction of core algorithmic techniques and proof strategies that underlie the best known provable guarantees for minimizing high dimensional convex functions. Focus on broad canonical optimization problems and survey results for efficiently solving them, ultimately providing the theoretical foundation for further study in optimization. In particular, focus will be on first-order methods for both smooth and non-smooth convex function minimization as well as methods for structured convex function minimization, discussing algorithms such as gradient descent, accelerated gradient descent, mirror descent, Newton's method, interior point methods, and more. Prerequisite: multivariable calculus and linear algebra.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 220: Probabilistic Analysis

Concepts and tools for the analysis of problems under uncertainty, focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, random variables, distributions, conditioning, expectation, change of variables, and limit theorems. Prerequisite: multivariable calculus and some linear algebra.
Terms: Aut, Sum | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 226: Fundamentals of Data Science: Prediction, Inference, Causality

This course is about understanding "small data": these are datasets that allow interaction, visualization, exploration, and analysis on a local machine. The material provides an introduction to applied data analysis, with an emphasis on providing a conceptual framework for thinking about data from both statistical and machine learning perspectives. Topics will be drawn from the following list, depending on time constraints and class interest: approaches to data analysis: statistics (frequentist, Bayesian) and machine learning; binary classification; regression; bootstrapping; causal inference and experimental design; multiple hypothesis testing. Class lectures will be supplemented by data-driven problem sets and a project. Prerequisites: CME 100 or MATH 51; 120, 220 or STATS 116; experience with R at the level of CME/STATS 195 or equivalent.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 231: Introduction to Computational Social Science (SOC 278)

With a vast amount of data now collected on our online and offline actions -- from what we buy, to where we travel, to who we interact with -- we have an unprecedented opportunity to study complex social systems. This opportunity, however, comes with scientific, engineering, and ethical challenges. In this hands-on course, we develop ideas from computer science and statistics to address problems in sociology, economics, political science, and beyond. We cover techniques for collecting and parsing data, methods for large-scale machine learning, and principles for effectively communicating results. To see how these techniques are applied in practice, we discuss recent research findings in a variety of areas. Prerequisites: introductory course in applied statistics, and experience coding in R, Python, or another high-level language.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 240: Accounting for Managers and Entrepreneurs (MS&E 140)

Non-majors and minors who have taken or are taking elementary accounting should not enroll. Introduction to accounting concepts and the operating characteristics of accounting systems. The principles of financial and cost accounting, design of accounting systems, techniques of analysis, and cost control. Interpretation and use of accounting information for decision making. Designed for the user of accounting information and not as an introduction to a professional accounting career. Enrollment limited. Admission by order of enrollment.
Terms: Aut, Win, Spr, Sum | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 252: Decision Analysis I: Foundations of Decision Analysis

Coherent approach to decision making, using the metaphor of developing a structured conversation having desirable properties, and producing actional thought that leads to clarity of action. Socratic instruction; computational problem sessions. Emphasis is on creation of distinctions, representation of uncertainty by probability, development of alternatives, specification of preference, and the role of these elements in creating a normative approach to decisions. Information gathering opportunities in terms of a value measure. Relevance and decision diagrams to represent inference and decision. Principles are applied to decisions in business, technology, law, and medicine. See 352 for continuation.
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 265: Introduction to Product Management

Product Managers define a product's functional requirements and lead cross functional teams responsible for development, launch, and ongoing improvement. Uses a learning-by-doing approach covering the following topics: changing role of a PM at different stages of the product life cycle; techniques to understand customer needs and validate demand; user experience design and testing; role of detailed product specifications; waterfall and agile methods of software development. Group projects involve the specification of a technology product though the skills taught are useful for a variety of product roles. No prior knowledge of design, engineering, or computer science required. Limited enrollment. Application deadlines: September 20, 2019 (for fall enrollment) and January 3, 2020 (for winter enrollment).
Terms: Aut, Win | Units: 3 | Grading: Letter (ABCD/NP)

MS&E 270: Strategy in Technology-Based Companies

For graduate students only. Introduction to the basic concepts of strategy, with emphasis on high technology firms. Topics: competitive positioning, resource-based perspectives, co-opetition and standards setting, and complexity/evolutionary perspectives. Limited enrollment. Students must attendnand complete an application at the first class session.
Terms: Aut | Units: 3-4 | Grading: Letter (ABCD/NP)

MS&E 273: Technology Venture Formation

Open to graduate students interested in technology driven start-ups. Provides the experience of an early-stage entrepreneur seeking initial investment, including: team building, opportunity assessment, customer development, go-to-market strategy, and IP. Teaching team includes serial entrepreneurs and venture capitalists. Student teams validate the business model using R&D plans and financial projections, and define milestones for raising and using venture capital. Final exam is an investment pitch delivered to a panel of top tier VC partners. In addition to lectures, teams interact with mentors and teaching team weekly. Enrollment by application: http://www.stanford.edu/class/msande273. Recommended: 270, 271, or equivalent.
Terms: Aut | Units: 3-4 | Grading: Letter (ABCD/NP)

MS&E 278: Patent Law and Strategy for Innovators and Entrepreneurs (ME 208)

This course teaches the essentials for a startup to build a valuable patent portfolio and avoid a patent infringement lawsuit. Jeffrey Schox, who is the top recommended patent attorney for Y Combinator, built the patent portfolio for Twilio (IPO), Cruise ($1B acquisition), and 300 startups that have collectively raised over $3B in venture capital. This course is equally applicable to EE, CS, and Bioengineering students. For those students who are interested in a career in Patent Law, please note that this course is a prerequisite for ME238 Patent Prosecution.
Terms: Aut | Units: 2-3 | Grading: Letter or Credit/No Credit
Instructors: ; Schox, J. (PI)

MS&E 293: Technology and National Security: Past, Present, and Future (INTLPOL 256, MS&E 193)

Explores the relation between technology, war, and national security policy from early history to modern day, focusing on current U.S. national security challenges and the role that technology plays in shaping our understanding and response to these challenges. Topics include the interplay between technology and modes of warfare; dominant and emerging technologies such as nuclear weapons, cyber, sensors, stealth, and biological; security challenges to the U.S.; and the U.S. response and adaptation to new technologies of military significance.
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 302: Fundamental Concepts in Management Science and Engineering

Each course session will be devoted to a specific MS&E PhD research area. Advanced students will make presentations designed for first-year doctoral students regardless of area. The presentations will be devoted to: illuminating how people in the area being explored that day think about and approach problems, and illustrating what can and cannot be done when addressing problems by deploying the knowledge, perspectives, and skills acquired by those who specialize in the area in question. Area faculty will attend and participate. During the last two weeks of the quarter groups of first year students will make presentations on how they would approach a problem drawing on two or more of the perspectives to which they have been exposed earlier in the class. Attendance is mandatory and performance will be assessed on the basis of the quality of the students¿ presentations and class participation. Restricted to first year MS&E PhD students.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit
Instructors: ; Giesecke, K. (PI)

MS&E 310: Linear Programming

Formulation of standard linear programming models. Theory of polyhedral convex sets, linear inequalities, alternative theorems, and duality. Variants of the simplex method and the state of art interior-point algorithms. Sensitivity analyses, economic interpretations, and primal-dual methods. Relaxations of harder optimization problems and recent convex conic linear programs. Applications include game equilibrium facility location. Prerequisite: MATH 113 or consent of instructor.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; Ye, Y. (PI); Li, X. (TA)

MS&E 319: Matching Theory

The theory of matching with its roots in the work of mathematical giants like Euler and Kirchhoff has played a central and catalytic role in combinatorial optimization for decades. More recently, the growth of online marketplaces for allocating advertisements, rides, or other goods and services has led to new interest and progress in this area. The course starts with classic results characterizing matchings in bipartite and general graphs and explores connections with algebraic graph theory, permanent, Pfaffian and counting and sampling matchings. Those results are complemented with models and algorithms developed for modern applications in market design, online advertising, and ride sharing. May be repeated for credit. Prerequisite: 212, CS 261, or equivalent.
Terms: Aut | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: ; Saberi, A. (PI)

MS&E 327: Topics in Causal Inference

This course introduces the fundamental ideas and methods in causal inference, and surveys a broad range of problems and applications. Emphasis will be on framing causal problems and identifying causal effects in both randomized experiments and observational studies. Topics will include: the potential outcomes framework; randomization-based inference and covariate adjustment; matching, and IPW; instrumental variables, regression discontinuity and synthetic ncontrols. Examples and applications will be taken from the fields of education, political science, economics, public health and digital marketing.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; Basse, G. (PI)

MS&E 366: Market Design and Resource Allocation in Non-Profit Settings

Survey of recent research on market design and resource allocation with a focus on under-explored domains in non-profit settings. Will start with classic results in allocation, matching and social choice, and discuss them in the context of relevant objectives such as social welfare and equity. Will then draw on techniques from operations research and economics to explore the design of resource allocation platforms in emerging applications including housing, humanitarian logistics, volunteer coordination, food allocation, conservation and sustainability, and informal markets in the developing world. Prerequisite: consent of instructor; background material will be covered throughout the course as necessary. May be repeated for credit.
Terms: Aut | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: ; Lo, I. (PI)

MS&E 370: Current Topics in Strategy, Innovation and Entrepreneurship

This course will cover focused exploration of contemporary readings and classics as relevant in strategy, innovation and entrepreneurship such as platforms, ecosystems, institutional logics, and strategic "games" in nascent markets. The course will include both content and methods discussions, including theory-building from multiple cases. PhD students only. Prerequisite: Consent of instructor.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: ; Eisenhardt, K. (PI)

MS&E 371: Innovation and Strategic Change

Doctoral research seminar, limited to Ph.D. students. Current research on innovation strategy. Topics: scientific discovery, innovation search, organizational learning, evolutionary approaches, and incremental and radical change. Topics change yearly. Recommended: course in statistics or research methods.
Terms: Aut, Win | Units: 1-3 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: ; Katila, R. (PI)

MS&E 389: Seminar on Organizational Theory (EDUC 375A, SOC 363A)

The social science literature on organizations assessed through consideration of the major theoretical traditions and lines of research predominant in the field. For PhD students only.
Terms: Aut | Units: 5 | Grading: Letter (ABCD/NP)
Instructors: ; Powell, W. (PI)

MS&E 391: Doctoral Research Seminar in Energy-Environmental Systems Modeling and Analysis

Restricted to PhD students, or by consent of instructor. Doctoral research seminar covering current topics in energy and environmental modeling and analysis. Current emphasis on approaches to incorporation of uncertainty and technology dynamics into complex systems models. May be repeated for credit.
Terms: Aut | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Weyant, J. (PI)

MS&E 408: Directed Reading and Research

Directed reading and research on a subject of mutual interest to student and faculty member. Available to undergraduate, master, and doctoral students. Student must clarify deliverables, units, and grading basis with faculty member before applicable deadlines. Prerequisite: consent of instructor
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit | Grading: Letter or Credit/No Credit

MS&E 454: Decision Analysis Seminar

Current research and related topics presented by doctoral students and invited speakers. May be repeated for credit. Prerequisite: 252.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Shachter, R. (PI)

MS&E 472: Entrepreneurial Thought Leaders' Seminar

Learn about entrepreneurship, innovation, culture, startups and strategy from a diverse lineup of accomplished leaders and entrepreneurs in venture capital, technology, education, philanthropy and more. Open to all Stanford students. Required weekly assignment. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

MS&E 494: The Energy Seminar (CEE 301, ENERGY 301)

Interdisciplinary exploration of current energy challenges and opportunities, with talks by faculty, visitors, and students. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Weyant, J. (PI)
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