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1 - 10 of 40 results for: MS&E

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 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 120: Introduction to Probability

Probability is the foundation behind many important disciplines including statistics, machine learning, risk analysis, stochastic modeling and optimization. This course provides an in-depth undergraduate-level introduction to fundamental ideas and tools of probability. Topics include: the foundations (sample spaces, random variables, probability distributions, conditioning, independence, expectation, variance), a systematic study of the most important univariate and multivariate distributions (Normal, Multivariate Normal, Binomial, Poisson, etc...), as well as a peek at some limit theorems (basic law of large numbers and central limit theorem) and, time permitting, some elementary markov chain theory. Prerequisite: CME 100 or MATH 51.
Terms: Aut | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

MS&E 120ACE: Introduction to Probability, ACE

Students attend MS&E 120 lectures with additional recitation sessions; two to four hours per week. Enrollment by permission only. Prerequisite: students should submit application for enrollment at: https://engineering.stanford.edu/students/programs/engineering-diversity-programs/additional-calculus-engineers before study list deadline. It is recommended students enroll in the regular section of MS&E 120 prior to submitting application. Corequisite: MS&E 120.
Terms: Aut | Units: 1
Instructors: Ahmed, R. (PI)

MS&E 134: Solving Social Problems with Data (COMM 140X, DATASCI 154, EARTHSYS 153, ECON 163, POLISCI 154, PUBLPOL 155, SOC 127)

Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including education & inequality, political polarization, and health equity & algorithmic design in the fall quarter, and social media, climate change, and school choice & segregation in the spring quarter. In-class exercises and problem sets will provide students with the opportunity to use more »
Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including education & inequality, political polarization, and health equity & algorithmic design in the fall quarter, and social media, climate change, and school choice & segregation in the spring quarter. In-class exercises and problem sets will provide students with the opportunity to use real-world datasets to discover meaningful insights for policymakers and communities. This course is the required gateway course for the new major in Data Science & Social Systems. Preference given to Data Science & Social Systems B.A. majors and prospective majors. Course material and presentation will be at an introductory level. Enrollment and participation in one discussion section is required. Sign up for the discussion section will occur on Canvas at the start of the quarter. Prerequisites: CS106A (required), DATASCI 112 (recommended as pre or corequisite). Limited enrollment. Please complete the interest form here: https://forms.gle/8ui9RPgzxjGxJ9k29. A permission code will be given to admitted students to register for the class.
Terms: Aut, Spr | Units: 5 | UG Reqs: WAY-SI, WAY-AQR

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 repeated for credit.
Terms: Aut, Win, Spr | Units: 1-2 | Repeatable 15 times (up to 30 units total)
Instructors: Borland, L. (PI)

MS&E 178: Entrepreneurship: Principles & Perspectives

This course uses the speakers from the Entrepreneurial Thought Leader seminar (MS&E472) to seed discussions around core topics in entrepreneurship. Students are exposed to a variety of guest speakers and lecturers. Topics change each quarter based on the speakers but cover foundational concepts: e.g. resilience, discovery, leadership, strategy, negotiations. Reflection and experiential exercises are used to augment learning. Enrollment limited to 60 students. See note for course application.
Terms: Aut, Win, Spr | Units: 2 | Repeatable for credit

MS&E 180: Organizations: Theory and Management

For undergraduates only. Classical and contemporary organization theory; the behavior of individuals, groups, and organizations. Limited enrollment; preference to declared MS&E majors and seniors from other departments.
Terms: Aut, Spr, Sum | Units: 4

MS&E 184: Flash Teams: Theory and Practice

Today's teams work in a world where experts are available everywhere all the time, where remote work has become a norm, and where data can be in-the-loop to guide team decisions. In this world, teams can become adaptive, augmented, and on-demand. This class equips students to understand and use this emerging form of collaboration - flash teams - by laying out the theory and practice involved in creating them. Already industries are being transformed by this new approach to teaming, and new opportunities, challenges, and responsibilities are arising. This class uses a practice-based workshop approach to help students develop the tools and understanding they need.
Terms: Aut | Units: 4

MS&E 193: Technology and National Security (INTLPOL 256)

Explores the relation between technology, war, and national security policy with reference to current events. Course focuses on current U.S. national security challenges and the role that technology plays in shaping our understanding and response to these challenges, including the recent Russia-Ukraine conflict. Topics include: 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
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