Python

Python Fundamentals: Parts 1-4

October 4, 2021, 12:00pm
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.

Python Fundamentals: Parts 1-4

October 26, 2021, 2:30pm
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.

Python Introduction to Machine Learning: Parts 1-2

September 27, 2021, 2:00pm
This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.

Forecasting Social Outcomes with Deep Neural Networks

October 7, 2025
Paige Park
by Paige Park. Our capacity to accurately predict social outcomes is increasing. Deep neural networks and artificial intelligence are crucial technologies pushing this progress along. As these tools reshape how social prediction is done, social scientists should feel comfortable engaging with them and meaningfully contributing to the conversation. But many social scientists are still unfamiliar with and sometimes even skeptical of deep learning. This tutorial is designed to help close that knowledge gap. We’ll walk step-by-step through training a simple neural network for a social prediction task: forecasting population-level mortality rates.

Maksymilian Jasiak

Data Science & AI Fellow 2025-2026
Civil and Environmental Engineering

Maksymilian Jasiak is a PhD Student in GeoSystems Engineering at the University of California, Berkeley. His research focuses on Distributed Fiber Optic Sensing (DFOS) for lifeline infrastructure monitoring. His work aims to advance critical infrastructure security and resilience. He holds a MS in GeoSystems Engineering from the University of California, Berkeley and a BS in Civil Engineering from the University of Illinois Urbana-Champaign.

Anusha Bishop

Consultant, Instructor
Department of Environmental Science, Policy, and Management

Anusha is a Ph.D. student in the Department of Environmental Science, Policy, and Management with a background in ecology and evolutionary biology. She is interested in genomics, spatial ecology, and computational biology. Currently, she conducts research on landscape and ecological genomics in the Wang Lab. She also has experience as a Teaching Assistant/Graduate Student Instructor for courses on statistics and data science as well as landscape ecology and environmental science methods.

Sohail Khan

Senior Data Science Fellow 2025-2026, Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Bruno Smaniotto

Senior Data Science Fellow 2025-2026, Data Science Fellow 2024-2025
Economics

I'm originally from Brazil, but I have been living in Berkeley for the last 5 years working towards my PhD in Economics. My main areas of interest are Behavioral and Macroeconomics, mostly their intersection, but I'm excited about learning and working on empirical applications on different fields.

Joyce Chen

Data Science & AI Fellow 2025-2026
College of Engineering

Joyce is a PhD candidate in Transportation Engineering. Her research focuses on assessing safety and network impacts of autonomous vehicles. She has teaching experiences in statistics and programming. Prior to Berkeley, Joyce obtained her Bachelor of Science in Computer Science from the University of Michigan, and had worked as a software engineer at various companies.

Jose Aguilar

Data Science & AI Fellow 2025-2026
Berkeley Graduate School of Education

Jose R. Aguilar is currently a PhD student in the Policy, Politics, and Leadership program at UC Berkeley’s School of Education. His research utilizes natural language processing, machine learning, and social network analysis to investigate how institutional discourse, algorithmic decision-making, and education policy influence postsecondary access and equity for marginalized students. Before Berkeley, Jose earned his M.A. in Urban Education from Loyola Marymount University and dual B.A./B.S.A. degrees in Government, Latina/o Studies, and Computer Science from the University of...