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1 - 10 of 162 results for: MS&E

MS&E 10SC: Artificial Intelligence and Deliberative Democracy

Deliberative democracy is a political theory that holds that democracy should be based on informed, respectful, and inclusive public deliberation. In this SoCo course, we explore the relationship between artificial intelligence (AI) and deliberative democracy, and examine how AI can be used to support and enhance the democratic process through deliberative democracy. This course will focus on the use of AI in the Stanford Online Deliberation Platform (a collaboration between the Crowdsourced Democracy Team and Deliberative Democracy Lab, both at Stanford), the ethics of AI and democracy, and the potential for AI to support deliberation and participation. The course will also explore the challenges and limitations of using AI in a democratic context and the need for effective regulation and governance of AI.
Terms: Sum | Units: 2

MS&E 20: Discrete Probability Concepts And Models

Fundamental 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, belief networks, random variables, conditioning, and expectation. The course is fast-paced, but it has no prerequisites.
Terms: Sum | Units: 4 | UG Reqs: WAY-FR
Instructors: Shachter, R. (PI)

MS&E 75: Redefining Creativity: Designing Human Connections in an AI World

With the recent developments in generative AI, the value in human creativity is increasingly a focus. Course draws from lessons from creativity in the arts to teach engineering students methods for creativity derived from musicians and artists. For our engineering students to learn creativity as a skill that is distinguishable and differentiated from generative artificial intelligence, this course explores, for instance the anatomy of a Hollywood pop song and the process behind the creation of globally impactful art. Students learn how to transfer these skills into the creation of engaging entrepreneurial solutions, for effective storytelling, and in developing their unique personal and professional stories. Students learn skills to unlock creative power which they will apply in the course as a design vehicle for a wide range of applications in engineering, self-expression, technological exploration, and the development of solutions that are centered around human connection and emotional engagement with the user. Sessions are practical, drawing tools and lessons from interdisciplinary individuals with wide-ranging careers. No artistic or entrepreneurial experience necessary.
Terms: Sum | Units: 3
Instructors: Hwang, R. (PI)

MS&E 79SI: Values and Principles in the Workplace: PEAK Fellows

Extension of the PEAK Fellows program. Serves as an opportunity for students to explore what it means to create and work for principled, entrepreneurial businesses. Through readings and peer-led discussions, students will definentheir personal set of values and principles to serve as a guide in shaping future teams and workplaces. Prerequisite: admission to PEAK Fellows Program. See https://stvp.stanford.edu/peak-fellows.
Terms: Aut | Units: 1
Instructors: Byers, T. (PI)

MS&E 92Q: International Environmental Policy

Preference to sophomores. Science, economics, and politics of international environmental policy. Current negotiations on global climate change, including actors and potential solutions. Sources include briefing materials used in international negotiations and the U.S. Congress.
Terms: Win | Units: 3
Instructors: Weyant, J. (PI)

MS&E 108: Senior Project

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.
Terms: Win | Units: 5

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

Formulation and computational analysis of linear, quadratic, and other convex optimization problems. Applications in machine learning, operations, marketing, finance, and economics. Prerequisite: CME 100 or MATH 51.
Terms: Aut | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR

MS&E 111DS: Introduction to Optimization: Data Science (MS&E 211DS)

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.
Terms: Win | Units: 3-4

MS&E 111X: Introduction to Optimization (Accelerated) (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: Spr | Units: 4 | UG Reqs: WAY-AQR

MS&E 112: Graph and Combinatorial Optimization (MS&E 212)

Optimization problems dealing with graph structure. Topics: introduction to graph theory; combinatorial optimization problems on networks including network flows, matching, and assignment problems; NP-completeness and approximation algorithms; applications in the study of social networks, market design, and bioinformatics. Prerequisites: basic concepts in linear algebra, probability theory, CS 106A or X.
Terms: Win | Units: 3
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