Python

Farnam Mohebi

Data Science Fellow
Haas School of Business

I am a PhD student at the Haas School of Business, University of California, Berkeley, and a researcher in the Department of Radiation Oncology at the University of California, San Francisco, having previously earned my MD and MPH degrees. My research focuses on the intersection of professionals and emerging technologies, drawing from the fields of medical sociology, organizational theory, and science and technology studies. I am particularly fascinated by the evolving relationship between physicians and artificial intelligence, the phenomenon of physician influencers, and the social...

More D-Lab events and workshops coming soon!

August 15, 2024, 9:00am

More workshops coming soon...

Please subscribe to the D-Lab weekly newsletter if you would like to be notified when new workshops are available for registering.

See event details for participation information.

Python Intermediate: Parts 1-3

June 17, 2024, 10:00am
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 Data Wrangling and Manipulation with Pandas

June 25, 2024, 10:00am
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

Python Machine Learning Fundamentals: Parts 1-2

June 25, 2024, 9:00am
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.

Python Fundamentals: Parts 1-3

June 11, 2024, 10:00am
This three-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 Web Scraping

June 26, 2024, 10:00am
In this workshop, we cover how to scrape data from the web using Python. Web scraping involves downloading a webpage's source code and sifting through the material to extract desired data.

Pratik Sachdeva, Ph.D.

Data/Research Scientist, Senior Consultant, and Senior Instructor

I am staff at the Social Sciences D-Lab. I received my Ph.D. in the Physics department at Berkeley. My research lies in the realm of theoretical/computational neuroscience, which aims to use mathematical and computational tools to better understand how neural systems operate and process information. My projects include using information-theoretic techniques to study how neural variability impacts information processing in neural circuits and investigating the statistical issues that impede the interpretation of parametric models of neural activity.

Beyond research, I'm...

Python Machine Learning Fundamentals: Parts 1-2

February 21, 2024, 9:00am
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.

Elijah Mercer

Consultant
School of Information

Elijah Mercer is a Master's student in the School of Information. He is particularly interested in using data to drive results for marginalized communities. His interests are in the field of criminal justice, policy and juvenile justice.