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CHEMENG 65Q: Chemical Engineering for Sustainability

Do you want to make the world more sustainable? How will we address the tremendous challenges that climate change brings? How can we reduce carbon emissions and not have huge disruptions in society? This class is for anyone who wants to create sustainable alternatives to what we use every day: engineers, scientists, those in humanities and the arts. Everyone has a role to play in designing our future. We will learn how to make the world more sustainable by exploring the exciting new world of (chemical) engineering sustainability. We will discuss renewable diesel and jet fuels; synthetic meat; compostable plastics; building materials that save energy; direct capture of carbon from the air; biological pharmaceuticals; and advanced recycling operations. The class starts with a brief overview of the deep cuts in carbon emissions and other pollutants that will be needed. Then, we focus on how sustainable (chemical) engineering can provide a solution, visiting four companies who are changing more »
Do you want to make the world more sustainable? How will we address the tremendous challenges that climate change brings? How can we reduce carbon emissions and not have huge disruptions in society? This class is for anyone who wants to create sustainable alternatives to what we use every day: engineers, scientists, those in humanities and the arts. Everyone has a role to play in designing our future. We will learn how to make the world more sustainable by exploring the exciting new world of (chemical) engineering sustainability. We will discuss renewable diesel and jet fuels; synthetic meat; compostable plastics; building materials that save energy; direct capture of carbon from the air; biological pharmaceuticals; and advanced recycling operations. The class starts with a brief overview of the deep cuts in carbon emissions and other pollutants that will be needed. Then, we focus on how sustainable (chemical) engineering can provide a solution, visiting four companies who are changing the world. Students will leave the class with an appreciation of how sustainable (chemical) engineering can help address climate change's substantial challenges, and perhaps an internship with one of the companies we visit. High school chemistry (balancing a chemical equation) and high school physics (unit conversions) are recommended for this course.
Terms: Win | Units: 3 | UG Reqs: WAY-AQR
Instructors: Libicki, S. (PI)

CME 106: Introduction to Probability and Statistics for Engineers (ENGR 155C)

Probability: random variables, independence, and conditional probability; discrete and continuous distributions, moments, distributions of several random variables. Numerical simulation using Monte Carlo techniques. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, non-parametric tests, regression and correlation analyses. Numerous applications in engineering, manufacturing, reliability and quality assurance, medicine, biology, and other fields. Prerequisite: CME100/ENGR154 or Math 51 or 52.
Terms: Win, Sum | Units: 4 | UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR

CME 108: Introduction to Scientific Computing

Introduction to Scientific Computing Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floating-point arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness. Implementation of numerical methods in MATLAB programming assignments. Prerequisites: CME 100, 102 or MATH 51, 52, 53; prior programming experience (MATLAB or other language at level of CS 106A or higher).
Terms: Aut | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

COLLEGE 105: The Politics of Development

This course examines foundational reasons for why some countries remain poor and why inequality persists today. In addition to answering the why question, we will also examine how practitioners, policy-makers, and academics have tackled global development challenges, where they have met success, and where failure has provided key lessons for the future. The course will examine issues of colonialism and contemporary foreign aid. Students will learn about and explore patterns of development across the world, critically evaluate foundational theories of development, and understand the practical challenges and possible solutions to reducing poverty, creating equality, and ensuring good governance. Course assignments will aim to have students practice linking data and evidence with policy innovation, using global datasets to perform statistical analyses. Students will leave this class with an understanding of how development works (and doesn't work) in practice.
Last offered: Spring 2023 | UG Reqs: College, THINK, WAY-AQR, WAY-SI

COMM 106: Communication Research Methods (COMM 206)

(Graduate students register for COMM 206. COMM 106 is offered for 5 units, COMM 206 is offered for 4 units.) Conceptual and practical concerns underlying commonly used quantitative approaches, including experimental, survey, content analysis, and field research in communication. Pre- or corequisite: STATS 60 or consent of instructor. (Cardinal Course certified by the Haas Center)
Terms: Aut | Units: 5 | UG Reqs: GER:DB-SocSci, WAY-AQR

COMM 138: Deliberative Democracy Practicum: Applying Deliberative Polling (COMM 238)

In this course, students will work directly on a real-world deliberative democracy project using the method of Deliberative Polling. Students in this course will work in partnership with the Center for Deliberative Democracy at Stanford, a research center devoted to the research in democracy and public opinion around the world. This unique practicum will allow students to work on an actual Deliberative Polling project on campus. In just one quarter, the students will prepare for, implement, and analyze the results for an Deliberative Polling project. This is a unique opportunity that allows students to take part in the entire process of a deliberative democracy project. Through this practicum, students will learn and apply quantitative and qualitative research methods. Students will explore the underlying challenges and complexities of what it means to actually do community-engaged research in the real world. As such, this course will provide students with skills and experience in rese more »
In this course, students will work directly on a real-world deliberative democracy project using the method of Deliberative Polling. Students in this course will work in partnership with the Center for Deliberative Democracy at Stanford, a research center devoted to the research in democracy and public opinion around the world. This unique practicum will allow students to work on an actual Deliberative Polling project on campus. In just one quarter, the students will prepare for, implement, and analyze the results for an Deliberative Polling project. This is a unique opportunity that allows students to take part in the entire process of a deliberative democracy project. Through this practicum, students will learn and apply quantitative and qualitative research methods. Students will explore the underlying challenges and complexities of what it means to actually do community-engaged research in the real world. As such, this course will provide students with skills and experience in research design in deliberative democracy, community and stakeholder engagement, and the practical aspects of working in local communities. This practicum is a collaboration between the Center for Deliberative Democracy and the Haas Center for Public Service. CDD website: http://cdd.stanford.edu; Hass Center website: https://haas.stanford.edu. Cardinal Course certified by the Haas Center for Public Service.
Terms: Aut | Units: 3-5 | UG Reqs: WAY-AQR, WAY-SI | Repeatable 3 times (up to 15 units total)
Instructors: Siu, A. (PI)

COMM 140X: Solving Social Problems with Data (DATASCI 154, EARTHSYS 153, ECON 163, MS&E 134, 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

CS 46: Working with Data: Delights and Doubts

The use of data to drive decisions and discoveries has increased dramatically over the past two decades, thanks to prevalent data collection, cheaper storage, faster computers, and sophisticated algorithms. This introductory seminar has three components: (1) Hands-on instruction in tools and techniques for working with data, from spreadsheets to data visualization systems to machine learning packages. This material is designed for students with little or no computer programming or data science experience. (2) A quarter-long "quantified self" project where students identify a set of questions about themselves or their surroundings, collect data to answer the questions, and analyze and visualize the collected data. (3) A set of guest speakers, including some who focus on the "doubts" of collecting and exploiting data, such as questions of ethics, bias, and privacy. In addition to the course project, students will complete short assignments to practice the learned tools and techniques, and will be expected to do some readings in advance of each guest speaker and engage in thoughtful discussion.
| UG Reqs: WAY-AQR

CS 102: Working with Data - Tools and Techniques

Aimed at non-CS undergraduate and graduate students who want to learn a variety of tools and techniques for working with data. Many of the world's biggest discoveries and decisions in science, technology, business, medicine, politics, and society as a whole, are now being made on the basis of analyzing data sets. This course provides a broad and practical introduction to working with data: data analysis techniques including databases, data mining, machine learning, and data visualization; data analysis tools including spreadsheets, Tableau, relational databases and SQL, Python, and R; introduction to network analysis and unstructured data. Tools and techniques are hands-on but at a cursory level, providing a basis for future exploration and application. Prerequisites: comfort with basic logic and mathematical concepts, along with high school AP computer science, CS106A, or other equivalent programming experience.
Last offered: Spring 2020 | UG Reqs: WAY-AQR

CS 109: Introduction to Probability for Computer Scientists

Topics include: counting and combinatorics, random variables, conditional probability, independence, distributions, expectation, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-AQR, WAY-FR, GER:DB-EngrAppSci
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