Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!
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This is an archive of our past training offerings. We are looking to include workshops on topics not yet covered here. Is there something not currently on the list? Send us a proposal.
An intro to the basics that instructors often assume you know, but that you probably never had good instruction on! After this course, you should be able to more easily start learning to program (e.g., in our R or Python Fundamentals series), follow instructions and documentation online (e.g., StackExchange), and communicate better with your collaborators who are programming.
This workshop will introduce participants to the use of qualitative data analysis (QDA) software and provide an overview of popular programs. This workshop is ideal for researchers who are new to the idea of using QDA software.
This non-technical workshop provides an overview of computational text analysis methods and tools. No experience in this area is expected or required. The goal is to provide an orientation for those wishing to go further with text analysis and interpret results of these methods.
This workshop offers a very basic introduction to qualitative research. First, an overview of the qualitative research process will be presented. Then, attendees will briefly explore (a) philosophical and conceptual considerations regarding research, (b) qualitative methodologies and methods, and (c) ways in which technology can aid the qualitative research process.
Since its creation in 1538, the Imprimerie Nationale in Paris has hosted non-Latin typefaces: among the treasures of its collection are the Grecs du Roy, cut by Claude Garamont between 1546–1550, and the Buis du Régent, 86,000 Chinese woodcut characters from 1715–1742.
This workshop will cover theory and techniques for maximizing the effectiveness of figures used for visualizing information. Rather than teaching any particular visualization software, this course will teach students about the "nuts and bolts" of effective data visualization.
This semester's TextXD event will be our biggest yet!
R FUN!damentals Part 4: For-loops and Functions
Students will learn how to write for-loops and functions in R. You will learn how to personalize functions via control structures such as ‘if’ and ‘else’. These learning objectives will be exemplified through introduction to the construction and graphical representation of Monte Carlo resampling simulation.
Are you trying to search for or clean up certain segments of text in your documents or data files, but it's taking hours to search and replace, because you have to type many slightly different versions of the keywords you're searching for? Perhaps you need to replace month names with just the first three letters, but you don't want to do this 12 times (once for each month), for lowercase, capit
Where and how can you access large collections of text for computational analysis? This session will outline the landscape of corpora available in the public domain and as library-licensed resources. We'll discuss licensing and copyright restrictions, as well as common modes of access and non-consumptive research tools provided by the HathiTrust Research Center, JSTOR, and more.
This three-part series will cover the following materials:
Part 1: Introduction
The Introduction to Smart Contracts workshop aims to paint a picture of what it's like to develop on the Ethereum Blockchain. In an effort to cater to all experience levels, the workshop will open with a module of contextual information and tools for those new to Ethereum and the general blockchain ecosystem.
Git is a powerful tool for keeping track of changes you make to the files in a project. You can use it to synchronize your work across computers, collaborate with others, and even deploy applications to the cloud. In this workshop, we'll learn the basics of understanding and using Git, including working with the popular "social coding" website, GitHub.
This workshop introduces Artificial Neural Networks (ANNs), a group of popular machine learning algorithms. No prior knowledge is required, though previous experience with other machine learning algorithms would be helpful. The workshop will be divided into three parts:
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.
This workshop has been cancelled. The workshop will be offered again during RRR week. Stay tuned for details. Our most sincere apologies for any inconvenience. Feel free to contact D-Lab's Qualitative Research Lead, Josué Meléndez Rodríguez, at melendez@berkeley.edu with any questions or concerns.
R FUN!damentals Part 3: Data Exploration and Analysis
Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.
This workshop will cover the basic concepts involved in georeferencing, or georectifiying, a digital image and provide hands-on practice using a web-based interface.
This three-part series will cover the following materials:
Part 1: Introduction