Overview
This three-part series will cover the following materials:
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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.
Overview
This three-part series will cover the following materials:
Overview
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 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.
Overview
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 for free at our R workshops!
D-Lab Infosession for the Visiting Scholar and Postdoc Affairs (VSPA) community. Come learn about all the resources and services D-Lab has to offer and see how you can get involved! We will give an overview of our workshops, trainings, consultations, and programs.
Overview
An introduction to programming basics in Bash and GitHub that are often assumed, but that you might have never had good instruction on!
Qualitative Data Analysis (QDA) software is used to organize and structure data, codes, memos, and other components of a qualitative study, as well as support engagement in analysis. This workshop is for qualitative researchers, new and established, interested in learning about MAXQDA, a software for which D-Lab provides substantive support. Assuming no prior knowledge in MAXQDA, this workshop will introduce participants to the website where the software can be downloaded and numerous training materials can be accessed.
*NOTE: Due to limited resources and staff, we are only able to offer workshops to UC Berkeley affiliates, partners (LBL, UCSF), and invited guests. We respectfully ask you not to register if you are not affliliated with UCB, LBL or UCSF.*
Overview
Geospatial data are an important component of social science and humanities data visualization and analysis.
Overview
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.
Overview
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 for free at our R workshops!
This workshop will be open to anyone interested in having the guidance, feedback and structure for writing a grant. Potential participants could be faculty who have not written an NIH grant before, postdocs or adjunct faculty, advanced graduate students, or even early stage graduate students who want to put together a dissertation grant.
Overview
An introduction to programming basics in Bash and GitHub that are often assumed, but that you might have never had good instruction on!
Overview
This three-part series will cover the following materials:
Overview
Geospatial data are an important component of social science and humanities data visualization and analysis.
Overview
Pandas is a Python package providing 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.
We plan to cover: