Data Science

Python Fundamentals: Parts 1-4

February 1, 2022, 2:00pm
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

R Fundamentals: Parts 1-4

March 8, 2022, 10:00am
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

Python Intermediate: Parts 1-3

October 9, 2023, 1:00pm
This three-part interactive workshop series teaches you intermediate programming Python for people with previous programming experience equivalent to our Python Fundamentals workshop. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Python Text Analysis: Topic Modeling

April 13, 2022, 3:00pm
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

Qualtrics Fundamentals

February 15, 2023, 5:00pm
Qualtrics is a powerful online tool available to Berkeley community members that can be used for a range of data collection activities. Primarily, Qualtrics is designed to make web surveys easy to write, test, and implement, but the software can be used for data entry, training, quality control, evaluation, market research, pre/post-event feedback, and other uses with some creativity.

R Fundamentals: Parts 1-4

December 4, 2023, 10:00am
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

Grace Hu

Data Science for Social Justice Fellow 2024
Bioengineering

Grace is a 3rd year Bioengineering PhD candidate in the joint UC Berkeley-UCSF Graduate Program. Her research lies at the nexus of computational design and 3D-bioprinting to advance tissue engineering for regenerative medicine. She previously studied Materials Science and Engineering (B.S.) and Computer Science (M.S.) at Stanford University, where she investigated printable batteries to power an ultra-affordable scanning electron microscope and explored computer science education research by developing AI models to augment teaching ability.

In her free time she...

Taylor Galdi

Data Science for Social Justice Fellow 2024
Law (JSP)
Sociology
Social Psychology

Taylor is a dual JD/Ph.D. student in Berkeley Law's Jurisprudence and Social Policy Program. Broadly, she is interested in studying courts, social movements and social change, and the legal profession.

Jonathan Pérez

Data Science for Social Justice Fellow 2024
Education

Jonathan Pérez is a 4th year PhD student in education with a designated emphasis critical theory. His research focuses on how students understand their radicalization with a focus particularly on how California's Ethnic Studies Curriculum can equip students to better make sense of how schools and society racialize them.

Outside of of UC Berkeley, Jonathan is an adjunct at San Francisco State University and works in curriculum design for The School of The New York Times.

Elizabeth Fajardo

Data Science for Social Justice Fellow 2024
Graduate Group in Ancient History and Mediterranean Archaeology

I am a PhD Student in Ancient History and Mediterranean Archaeology. I study the Roman Imperial Economy, particularly the development of human capital during the Imperial Period and the Roman monetary system.

My main research interests include political economy, labor, and economic metaphor in Ancient Rome, particularly highlighting the intersections of economic production and power.