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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.
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.
Part 3 Topics:
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!
This hands on workshop builds on part 2 by introducing the basics of Python's scikit-learn package to implement unsupervised text analysis methods. This workshop will cover a) vectorization and Document Term Matrices, b) weighting (tf-idf), and c) uncovering patterns using topic modeling.
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.
Part 2 Topics:
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!
This hands on workshop goes through the common “preprocessing recipe” that is used as the foundation for a variety of other applications as well as some basic natural language processing techniques. These include: a) digitization (utf 8), b) removal of stopwords, numbers, punctuation, c) tokenization, d) calculation of word frequencies / proportions, e) part of speech tagging, and f) concordan
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.
Part 1 Topics:
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!
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.
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 R or python), follow instructions and documentation online (e.g., StackExchange), and communicate better with your collaborators who are programming. This interactive workshop will cover:
This workshop will introduce methods and libraries for mapping spatial data in R.
This workshop will demonstrate the capabilities of the GeoPandas library for working with spatial data & creating maps in python. We will begin with an introduction to spatial data and progress to mapping and basic geoprocessing and analysis. We will also introduce geocoding as a way to create spatial data.
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.
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!
Join the Qualitative Methods Group for a conversation with Ph.D. candidate Robert Connell on participatory research. Mr. Connell will be sharing how he used elements of participatory research methodology in his dissertation field research.
This workshop will provide an introduction to spatial analysis in R. After a brief review of spatial data types in R we will geocode a set of addresses and then ask spatial questions of those locations. For example, we might ask what school district is a location within, how many locations are within X distance of each shool, or what is the census tract id for a location.
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.
Part 3 Topics:
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!
This hands on workshop builds on part 2 by introducing the basics of Python's scikit-learn package to implement unsupervised text analysis methods. This workshop will cover a) vectorization and Document Term Matrices, b) weighting (tf-idf), and c) uncovering patterns using topic modeling.
A basic familiarity with Python is required if you wish to follow along with the tutorial.
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.
Part 2 Topics:
