Programming Languages

Python Fundamentals: Parts 1-4

September 7, 2021, 11:00am
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.
Registration is unavailable.

Geospatial Fundamentals with QGIS: Parts 1-2

September 17, 2021, 10:00am
This workshop will introduce methods for working with geospatial data in QGIS, a popular open-source desktop GIS program that runs on both PCs and Macs as well as linux computers. Participants will learn how to load, query and visualize point, line and polygon data. We will also introduce basic methods for processing spatial data, which are the building blocks of spatial analysis workflows. Coordinate reference systems and map projections will also be introduced.

R Fundamentals: Parts 1-4

September 7, 2021, 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.
Registration is unavailable.

R Bootcamp: Fall 2021

August 21, 2021, 8:30am
The workshop will be an intensive two-day introduction to R using RStudio. After the first morning session, the workshop will (staffing permitting) be split into two separate tracks. Co-sponsored by the UC Berkeley Statistics Department and the D-Lab.
See event details for participation information.

Python Fundamentals: Parts 1-4

August 19, 2021, 1:00pm
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.
Registration is unavailable.

R Fundamentals: Parts 1-4

August 19, 2021, 9:30am
Data are the foundations of the social and biological sciences and humanities. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. This workshop will teach you to use base R to build a programming vocabulary to develop and train your data skills! The D-Lab's R Fundamentals 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.
Registration is unavailable.

Why Teaching Social Scientists How To Code Like A Professional Is Important

September 23, 2020
Jae Yeon Kim, Ph.D.

I use data science to study political learning, organization, and mobilization among marginalized populations. I have always loved programming and want to serve people lacking voice and representation in a society. I am blessed to have found and chosen computational social science—a field situated between social science and data science—as my main research area.

I also love teaching people how to code, especially social scientists, and I take that mission seriously. I have taught computational tools and techniques at both graduate and undergraduate levels in semester-...

Projects as a Learning Tool

April 6, 2021
Emily Grabowski

Let’s say you’re new to programming, or maybe you’ve coded before but you’re tackling a new concept. You’ve read a blog post or taken a workshop, and have a general sense of what is going on. But how do you take this to the next level? One of my favorite ways to dive into a new technique is to simply try it out.

With coding, learning by doing is one of the best ways to improve. When I started learning Python, I took a class where I did homework assignments involving coding small games and algorithms. While these were useful for general coding, I wanted to dig in to the...

Organized Code Repositories Accelerate Science and Facilitate Reproducubility

March 2, 2021
Pratik Sachdeva, Ph.D.

Computational and data-driven research increasingly requires developing complex codebases. At the same time, many scientists don’t receive training in software engineering practices, resulting in, for some, the perception that scientists write terrible software. As scientists, good software should accelerate our work and facilitate its reproducibility. While building good coding practices takes some time and experience, it doesn’t require a...

Visuals for Everyone: An Exercise on the Importance of Intuitive Data Visualization

March 30, 2021
Daphne Yang

A couple years ago, I took an undergraduate biostatistics course here at UC Berkeley and vividly remember one of the first discussion section activities on interpreting data and visualizations. From this activity, I learned about why, as data consumers, we must always be aware of not only what visualizations are really representing but also understanding where the data is really coming from. While this might seem obvious, this has been one of the most valuable lessons as an aspiring data scientist/enthusiast. I learned the importance of analyzing and understanding data with...