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1 - 10 of 68 results for: CARDCOURSES::eng

AFRICAAM 389C: Race, Ethnicity, and Language: Black Digital Cultures from BlackPlanet to AI (CSRE 385, EDUC 389C, PWR 194AJB)

This seminar explores the intersections of language and race/racism/racialization in the public schooling experiences of students of color. We will briefly trace the historical emergence of the related fields of sociolinguistics and linguistic anthropology, explore how each of these scholarly traditions approaches the study of language, and identify key points of overlap and tension between the two fields before considering recent examples of inter-disciplinary scholarship on language and race in urban schools. Issues to be addressed include language variation and change, language and identity, bilingualism and multilingualism, language ideologies, and classroom discourse. We will pay particular attention to the implications of relevant literature for teaching and learning in urban classrooms.
Terms: Win | Units: 3-4
Instructors: Banks, A. (PI)

ALP 301: Data-Driven Impact

This is a team-based course where students will work on a project to improve a product using data and experimentation. We will cover key considerations for designing and executing high-quality research for product innovation to drive business outcomes and social impact. Students will have the opportunity to apply methods from machine learning and causal inference to a real-world scenario provided by a partner organization. Topics include designing research and experiments, data analysis, experimental and non-experimental methods for estimating the impact of product features, as well as management consideration for the delivery of actionable research. The course involves three weekly meetings: two lectures and one lab. Lectures will focus on research methods and will provide examples of research outputs for students to discuss and evaluate. Labs will comprise technical training in data analysis and structured team meetings. Students will work in cross-functional teams of 5-6 with milestones throughout the quarter. The final deliverable will be a presentation that highlights the team's work and delivers actionable recommendations that draw from the team's research. The class will include a mix of students with different backgrounds and skills. Each team will have at least one member with significant experience with data analysis. This course is part of the GSB's new Action Learning Program, in which you will work on real business challenges under the guidance of faculty. In this intensive project-based course, you will: Learn research-validated foundations, tools, and practices, Apply these tools and learnings to a real project for an external organization, Create value for the organization by providing insights and deliverables, Be an ambassador to the organization by exposing them to the talent, values, and expertise of the GSB. You will also have the opportunity to: Gain practical industry experience and exposure to the organization, its industry, and the space in which it operates, Build relationships in the organization and industry, and gain an understanding of related career paths. Prerequisites: Some experience with statistical analysis and the R statistical package. Students with less experience will have an opportunity to catch up through tutorials provided through the course. Non-GSB students are expected to have an advanced understanding of tools and methods from data science and machine learning as well as a strong familiarity with R, Python, SQL, and other similar high-level programming languages. (Cardinal Course certified by the Haas Center)
Last offered: Spring 2021

ALP 308: Designing Experiments for Impact

This is a team-based course where students will work on a project to design and carry out an experiment intended to drive social impact in collaboration with a partner organization. The first few weeks will include lectures, hands-on tutorials, and labs designed to guide students through the process of experimental design in the digital context. Special topics include designing and selecting outcome measures that capture the impact of interventions; multi-stage experiments with applications to chatbots; learning how treatment effects vary across subgroups; adaptive experiments using bandits and artificial intelligence; and estimation of policies that target treatments based on subject characteristics. Experiments may be conducted on the customer base of a partner organization through their digital applications or on recruited subjects, such as subjects recruited to interactive chatbots. The teaching team will provide templates and technical assistance for designing and running the experiments. Students from different disciplinary backgrounds will be assigned roles to work in teams on the project. This course is part of the GSB's Action Learning Program, in which you will work on real business challenges under the guidance of faculty. In this intensive project-based course, you will learn research-validated foundations, tools, and practices; apply these tools and learnings to a real project for an external organization; create value for the organization by providing insights and deliverables; and be an ambassador to the organization by exposing them to the talent, values, and expertise of the GSB. You will also have the opportunity to gain practical industry experience and exposure to the organization, its industry, and the space in which it operates; build relationships in the organization and industry; and gain an understanding of related career paths. Prerequisites: Some experience with statistical analysis and the R statistical package. Students with less experience will have an opportunity to catch up through tutorials provided through the course. Non-GSB students are expected to have an advanced understanding of tools and methods from data science and machine learning as well as a strong familiarity with R, Python, SQL, and other similar high-level programming languages. Cardinal Course certified by the Haas Center.
Last offered: Spring 2022

BIOE 271: Frugal Science

As a society, we find ourselves surrounded by planetary-scale challenges ranging from lack of equitable access to health care to environmental degradation to dramatic loss of biodiversity. One common theme that runs across these challenges is the need to invent cost-effective solutions with the potential to scale. The COVID-19 pandemic provides yet another example of such a need. In this course, participants will learn principles of frugal science to design scalable solutions with a cost versus performance rubric and explore creative means to break the accessibility barrier. Using historic and current examples, we will emphasize the importance of first-principles science to tackle design challenges with everyday building blocks. Enrollment is open to all Stanford students from all schools/majors, who will team up with collaborators from across the globe to build concrete solutions to planetary-scale challenges. Come learn how to solve serious challenges with a little bit of play.
Terms: Win | Units: 4

CEE 124X: Shaping the Future of the Bay Area (CEE 224X)

Note to students: please be advised that the course number for this course has been changed to: CEE 218X, which is offered Autumn 2019-20. If you are interested in taking this course, please enroll in CEE 218X instead for Autumn 2019-20.
Last offered: Autumn 2019

CEE 218Y: Shaping the Future of the Bay Area (EPS 118Y, EPS 218Y, ESS 118Y, ESS 218Y, GEOPHYS 118Y, GEOPHYS 218Y, POLISCI 118Y, PUBLPOL 118Y, PUBLPOL 218Y)

(Formerly GEOLSCI 118Y and 218Y) The complex urban problems affecting quality of life in the Bay Area, from housing affordability and transportation congestion to economic vitality and social justice, are already perceived by many to be intractable, and will likely be exacerbated by climate change and other emerging environmental and technological forces. Reforming urban systems to improve the equity, resilience and sustainability of communities will require new collaborative methods of assessment, goal setting, and problem solving across governments, markets, and communities. It will also require academic institutions to develop new models of co-production of knowledge across research, education, and practice. This XYZ course series is designed to immerse students in co-production for social change. The course sequence covers scientific research and ethical reasoning, skillsets in data-driven and qualitative analysis, and practical experience working with local partners on urban chal more »
(Formerly GEOLSCI 118Y and 218Y) The complex urban problems affecting quality of life in the Bay Area, from housing affordability and transportation congestion to economic vitality and social justice, are already perceived by many to be intractable, and will likely be exacerbated by climate change and other emerging environmental and technological forces. Reforming urban systems to improve the equity, resilience and sustainability of communities will require new collaborative methods of assessment, goal setting, and problem solving across governments, markets, and communities. It will also require academic institutions to develop new models of co-production of knowledge across research, education, and practice. This XYZ course series is designed to immerse students in co-production for social change. The course sequence covers scientific research and ethical reasoning, skillsets in data-driven and qualitative analysis, and practical experience working with local partners on urban challenges that can empower students to drive responsible systems change in their future careers. The Autumn (X) and Winter (Y) courses are focused on basic and advanced skills, respectively, and completion is a prerequisite for participation in the Spring (Z) practicum quarter, which engages teams in real-world projects with Bay Area local governments or community groups. X and Y are composed of four weekly pedagogical components: (A) lectures; (B) writing prompts linked with small group discussion; (C) lab and self-guided tutorials on the R programming language; and (D) R data analysis assignments. Open to undergraduate and graduate students in any major. For more information, visit http://bay.stanford.edu/education. Cardinal Course certified by the Haas Center. Change of Department Name: Earth and Planetary Science (Formerly Geologic Sciences).
Terms: Win | Units: 1-5 | Repeatable 2 times (up to 10 units total)

CEE 218Z: Shaping the Future of the Bay Area (EPS 118Z, EPS 218Z, ESS 118Z, ESS 218Z, GEOPHYS 118Z, GEOPHYS 218Z, POLISCI 118Z, PUBLPOL 118Z, PUBLPOL 218Z)

(Formerly GEOLSCI 118Z and 218Z) Students are placed in small interdisciplinary teams (engineers and non-engineers, undergraduate and graduate level) to work on complex design, engineering, and policy problems presented by external partners in a real urban setting. Multiple projects are offered and may span both Winter and Spring quarters; students are welcome to participate in one or both quarters. Students are expected to interact professionally with government and community stakeholders, conduct independent team work outside of class sessions, and submit deliverables over a series of milestones. Prerequisite: the Autumn (X) skills course or approval of instructors. For information about the projects and application process, visit http://bay.stanford.edu. Cardinal Course certified by the Haas Center. Change of Department Name: Earth and Planetary Science (Formerly Geologic Sciences).
Terms: Spr | Units: 1-5 | Repeatable 2 times (up to 10 units total)

CEE 224X: Shaping the Future of the Bay Area (CEE 124X)

Note to students: please be advised that the course number for this course has been changed to: CEE 218X, which is offered Autumn 2019-20. If you are interested in taking this course, please enroll in CEE 218X instead for Autumn 2019-20.
Last offered: Autumn 2019

CEE 265F: Environmental Governance and Climate Resilience (POLISCI 227B, PUBLPOL 265F, SUSTAIN 248)

Adaptation to climate change will not only require new infrastructure and policies, but it will also challenge our local, state and national governments to collaborate across jurisdictional lines in ways that include many different types of private and nonprofit organizations and individual actors. The course explores what it means for communities to be resilient and how they can reach that goal in an equitable and effective way. Using wildfires in California as a case study, the course assesses specific strategies, such as controlled burns and building codes, and a range of planning and policy measures that can be used to enhance climate resilience. In addition, it considers how climate change and development of forested exurban areas (among other factors) have influenced the size and severity of wildfires. The course also examines the obstacles communities face in selecting and implementing adaptation measures (e.g., resource constraints, incentives to develop in forested areas, inad more »
Adaptation to climate change will not only require new infrastructure and policies, but it will also challenge our local, state and national governments to collaborate across jurisdictional lines in ways that include many different types of private and nonprofit organizations and individual actors. The course explores what it means for communities to be resilient and how they can reach that goal in an equitable and effective way. Using wildfires in California as a case study, the course assesses specific strategies, such as controlled burns and building codes, and a range of planning and policy measures that can be used to enhance climate resilience. In addition, it considers how climate change and development of forested exurban areas (among other factors) have influenced the size and severity of wildfires. The course also examines the obstacles communities face in selecting and implementing adaptation measures (e.g., resource constraints, incentives to develop in forested areas, inadequate policy enforcement, and weak inter-agency coordination). Officials from various Bay Area organizations contribute to aspects of the course; and students will present final papers to local government offcials. Limited enrollment. Students will be asked to prepare application essays on the first day of class. Course is intended for seniors and graduate students.
Terms: Win | Units: 3

CME 99: WiDS Datathon Independent Study (DATASCI 197)

This independent study offers students the opportunity to participate in the WiDS Datathon for 1-unit of credit. The WiDS Datathon is an annual and global event that encourages data scientists of all levels to discover and hone their data science skills while solving an interesting and critical social impact challenge. The 2023 Challenge, "Data Science for Subseasonal Forecast", centers on climate change and is in partnership with Climate Change AI (CCAI). Accurate long-term forecasts of temperature and precipitation is crucial for mitigating the effects of climate change (i.e. preparing for droughts and other wet weather extremes). Such forecasts can potentially impact many industries (e.g. agriculture, energy, disaster planning) in countries across the globe. Currently, purely physics-based models dominate short-term weather forecasting. But these models have a limited forecast horizon. The availability of meteorological data offers an opportunity for data scientists to improve subseasonal forecasts by blending physics-based forecasts with machine learning. To learn more, visit: https://www.widsconference.org/datathon.htmlStudents may participate in this independent study in teams of 1-4. To qualify for official participation in the datathon, at least half of each team must identify as women. To receive credit, the team will participate in the Datathon and write a report detailing their submission and reflecting on their experience. Interested students should register for the course, and sign up as a team using this form: https://forms.gle/LyX3yNU7dLnTCux1A. To find other students interested in forming a team, go here: https://docs.google.com/presentation/d/1UvutEFtYFeCkLkwnpU01R5V5WmJeMi4kVkaZYHxSiAY/edit?usp=sharing
Last offered: Winter 2023 | Repeatable 4 times (up to 4 units total)
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