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11 - 20 of 46 results for: SOC ; Currently searching autumn courses. You can expand your search to include all quarters

SOC 192: Undergraduate Research Apprenticeship

Work in an apprentice-like relationship with faculty on an on-going research project. Prior arrangement required.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable for credit

SOC 193: Undergraduate Teaching Apprenticeship

Prior arrangement required.
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable for credit

SOC 194: Computational Undergraduate Research

Computational sociology research working with faculty on an on-going technical research project. Applications for position reviewed on a rolling basis.
Terms: Aut, Win, Spr | Units: 1-5 | Repeatable for credit

SOC 196: Senior Thesis

Work on an honors thesis project under faculty supervision (see description of honors program). Must be arranged early in the year of graduation or before.
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit

SOC 204: Capstone Research Seminar

Terms: Aut | Units: 5
Instructors: Hwang, J. (PI)

SOC 214: Economic Sociology (SOC 114)

(Graduate students register for 214.) The sociological approach to production, distribution, consumption, and markets, emphasizing the impact of norms, power, social structure, and institutions on the economy. Comparison of classic and contemporary approaches to the economy among the social science disciplines. Topics: consumption, labor markets, organization of professions such as law and medicine, the economic role of informal networks, industrial organization, including the structure and history of the computer and popular music industries, business alliances, capitalism in non-Western societies, and the transition from state socialism in E. Europe and China.
Terms: Aut | Units: 4

SOC 226: Introduction to Social Networks (SOC 126)

(Graduate students register for 226.) Theory, methods, and research. Concepts such as density, homogeneity, and centrality; applications to substantive areas. The impact of social network structure on individuals and groups in areas such as communities, neighborhoods, families, work life, and innovations.
Terms: Aut, Spr | Units: 4
Instructors: Hahn, M. (PI)

SOC 254C: The Politics of Algorithms (COMM 154, COMM 254, CSRE 154T, SOC 154)

Algorithms have become central actors in today's digital world. In areas as diverse as social media, journalism, education, healthcare, and policing, computing technologies increasingly mediate communication processes. This course will provide an introduction to the social and cultural forces shaping the construction, institutionalization, and uses of algorithms. In so doing, we will explore how algorithms relate to political issues of modernization, power, and inequality. Readings will range from social scientific analyses to media coverage of ongoing controversies relating to Big Data. Students will leave the course with a better appreciation of the broader challenges associated with researching, building, and using algorithms.
Terms: Aut | Units: 4-5
Instructors: Christin, A. (PI)

SOC 256A: The Changing American City (CSRE 156, SOC 156A, URBANST 156A)

After decades of decline, U.S. cities today are undergoing major transformations. Young professionals are flocking to cities instead of fleeing to the suburbs. Massive increases in immigration have transformed the racial and ethnic diversity of cities and their neighborhoods. Public housing projects that once defined the inner city are disappearing, and crime rates have fallen dramatically. Do these changes signal the end of residential segregation and urban inequality? Who do these changes benefit? This course will explore these issues and strategies to address them through readings and discussion, analyzing a changing neighborhood in a major city in the Bay Area in groups (which will include at least one site visit), and studying a changing neighborhood or city of their choice for their final project. The course does not have pre-requisites.
Terms: Aut | Units: 4
Instructors: Hwang, J. (PI)

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

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
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