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PRIVATE! Python Fundamentals: Part 4

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.

NOTE: This is not a quantitative workshop, but instead a how-to-use-Python workshop. However, you will find that after completing this series you will have the skills to code quantitative tasks. 

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PRIVATE! Python Fundamentals: Part 3

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. 

NOTE: This is not a quantitative workshop, but instead a how-to-use-Python workshop. However, you will find that after completing this series you will have the skills to code quantitative tasks.  

Log in to register for this training.

PRIVATE! Python Fundamentals: Part 2

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. 

NOTE: This is not a quantitative workshop, but instead a how-to-use-Python workshop. However, you will find that after completing this series you will have the skills to code quantitative tasks. 

Log in to register for this training.

PRIVATE! Python Fundamentals: Part 1

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.

NOTE: This is not a quantitative workshop, but instead a how-to-use-Python workshop. However, you will find that after completing this series you will have the skills to code quantitative tasks. 

Log in to register for this training.

CANCELLED! Machine Learning in Python

** This workshop has been cancelled and will be rescheduled.**

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.

Prior knowledge: We will assume a basic knowledge of Python and a basic understanding of machine learning techniques. No theory instruction will be provided.

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R Bootcamp

Co-sponsored by the UC Berkeley Statistics Department, D-Lab, and the Statewide Database at Berkeley Law.

The workshop will be an intensive two-day introduction to R using RStudio. After the first morning session, the workshop will be split into two separate tracks. Topics will include

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Hate that defines us

Posted: May, 06, 2019

By: Simal Ozen Irmak

In 2018, according to a survey conducted on behalf of the Anti-defamation League, 53% of Americans experienced some form of online hate speech.

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Collaborative & Reproducible Research as a (Semi) Independent Researcher

Posted: Apr, 30, 2019

By: Ijeamaka Anyene

As I started graduate school, I received the opportunity to become part of a research group working on the prevention of mother-to-child transmission of HIV. Quickly I discovered that being part of a research group requires a lot of independent research. But that independent research is not quite so independent. Instead my main collaborator when it came to code review and continuation of work, was myself. However, it was not myself at the time the analysis was conducted, it was myself two weeks later trying to build on my previous work.

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Machine Learning in Python

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.

Prior knowledge: We will assume a basic knowledge of Python and a basic understanding of machine learning techniques. No theory instruction will be provided.

Log in to register for this training.

The available spaces and the waitlist for this event are both full.

Working with Data to Explore Transportation and Society

Posted: Apr, 23, 2019

By: Sergio Castellanos

One of the great things about the D-Lab is the ability to engage with students and researchers from different backgrounds and learn from their approaches to doing research and answering interesting questions.  A project I’m quite excited in growing with the D-Lab community to include broader perspectives is one related to transportation in cities.

 

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